Socio-Economic Burden of Disease: The COVID-19 Case

Author: Tomé, Eduardo; Garavan, Thomas; Dias, Ana

Publisher: Basel: MDPI - Multidisciplinary Digital Publishing Institute

Year: 2024

DOI: 10.3390/books978-3-7258-0290-6

Source: https://www.econstor.eu/bitstream/10419/305342/1/MDPI_9783725802890.pdf

Tomé, Edua do (Ed.); Ga a an, Thomas (Ed.); Dias, Ana (Ed.)
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Socio-Economic Bu den o Disease: The COVID-19 Case
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Economic Bu den o Disease: The COVID-19 Case, ISBN 978-3-7258-0290-6, MDPI - Mul idisciplina y
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Special Issue Rep in
Socio-Economic Bu den
o Disease
The COVID-19 Case
Edi ed by
Edua do Tomé, Thomas Ga a an and Ana Dias
Socio-Economic Bu den o Disease:
The COVID-19 Case
Socio-Economic Bu den o Disease:
The COVID-19 Case
Edi o s
Edua do Tom´e
Thomas Ga a an
Ana Dias
Basel •Beijing •Wuhan •Ba celona •Belg ade •No i Sad •Cluj •Manches e

Edi o s
Edua do Tom´
e
Uni e sidade Lus´
o ona
Lisboa
Po ugal
Thomas Ga a an
Uni e si y College Co k
Co k
I eland
Ana Dias
Uni e sidade de A ei o
A ei o
Po ugal
Edi o ial O ﬁce
MDPI
S . Alban-Anlage 66
4052 Basel, Swi ze land
This is a ep in o a icles om he Special Issue published online in he open access jou nal
Heal hca e (ISSN 2227-9032) (a ailable a : h ps://www.mdpi.com/jou nal/heal hca e/special
issues/socio-economic bu den o disease co id-19 case).
Fo ci a ion pu poses, ci e each a icle independen ly as indica ed on he a icle page online and as
indica ed below:
Las name, A.A.; Las name, B.B. A icle Ti le. Jou nal Name Yea ,Volume Numbe , Page Range.
ISBN 978-3-7258-0289-0 (Hbk)
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Abou he Edi o s
Edua do Tom´e
Edua do Tom´
e B Econ, M Econ, PhD, is an ac i e esea che and eache in he domain o he
economics o human esou ces. He also plays an impo an ole in he ne wo k o esea ch among
ac i e Eu opean academics in his ﬁeld o s udy. To da e, he has au ho ed o co-au ho ed 64 pape s
published in pee - e iewed jou nals and 115 pape s in pee - e iewed con e ence p oceedings. He has
also au ho ed 15 book chap e s. He is also a membe o he Edi o ial Boa d o se e al pee - e iewed
jou nals. He has ecei ed se e al Honou s, including wo P izes o Scien iﬁc Achie emen . Edua do
Tome eaches a a ie y o subjec s on bo h unde g adua e and pos -g adua e p og ammes. He is
also ac i e as a supe iso , wo king wi h unde g adua es, mas e ’s s uden s and PhD s uden s.
He is no ed o his success wi h bo h mas e ’s and doc o al s uden s. He also lec u es on a PhD
p og amme, and is equally com o able eaching in bo h Po uguese and English. He can also
speak, ead and w i e in F ench and Spanish. Long be o e COVID-19, he used online pla o ms
(emails, Moodle, Blackboa d, Skype, e c) as a complemen a y o m o communica ion wi h s uden s
and colleagues, a si ua ion ha has been made essen ial a e he pandemic. Edua do Tome has
a signiﬁcan p esence among he academic communi y in gene al, and especially among hose
in e es ed in in angibles. Since 2009, he has o ganized well-a ended in e na ional con e ences
o his uni e si y on hemes such as knowledge managemen , human esou ce de elopmen , and
in ellec ual capi al. Wi h iends, he c ea ed he TAKECon e ence, which has been held e e y yea
since 2016, wi h he excep ion o 2020. These con e ences ha e augmen ed he ex e nal ocus and
in e na ional ela ionships o his ac i i ies. All con e ences ha e esul ed in spin-o s such as Special
Issues in jou nals. These e en s ha e b ough bo h p es ige and ﬁnancial ewa ds o he uni e si y.
Cu en ly, he is a membe o he GOVCOPP o Uni e sidade de A ei o, In epid o UTAD and eaches
a Uni e sidade Luso ona.
Thomas Ga a an
Thomas Ga a an is P o esso o Leade ship P ac ice in CUBS, UCC. He was ecen ly lis ed in he
S an o d Uni e si y Science-Wide au ho ci a ion indica o s 2020 as one o he op 2% o academics
in Economics and Business. He is a wo ld leading expe in leade ship de elopmen , lea ning and
de elopmen and HRD. He has published 185 jou nal a icles, 16 books, 26 book chap e s and 6
monog aphs. He has published ex ensi ely in leading HRD jou nals including HRDQ, HRDR, ADHR
and HRDI. He has also published ex ensi ely in he op ou HRM jou nals: HRM (US) HRMJ,
Pe sonnel Re iew and IJHRM. In addi ion, he has published ex ensi ely in managemen jou nals
including he In e na ional Jou nal o Managemen Re iews, Eu opean Managemen Re iew, Jou nal
o Business Resea ch, Tou ism Managemen , In o ma ion Technology and People, In e na ional
Small Business Jou nal, Thunde bi d In e na ional Re iew and he Jou nal o Sleep Resea ch and
Business E hics: A Eu opean Re iew. His mos ecen book publica ions include Lea ning and
De elopmen in O ganiza ions: A Sys ems-In o med Model o E ec i eness (Palg a e), S a egic Human
Resou ce Managemen (Ox o d Uni e si y P ess), Handbook o In e na ional Human Resou ce De elopmen
(Edwa d Elga ) and Global Human Resou ce De elopmen (Rou ledge). He is co-edi o o he Eu opean
Jou nal o T aining and De elopmen and Associa e Edi o o Pe sonnel Re iew and is a membe
o he HRDQ, HRDI, HRDR, ADHR, HRMJ, In e na ional Jou nal o T aining and De elopmen and
In e na ional Jou nal o Human Resou ce Managemen . He has ex ensi e eaching expe ience wi h
unde g adua e, pos -g adua e and pos -expe ience s uden s, in addi ion o execu i e educa ion and
leade ship de elopmen . He was ecen ly elec ed o he Hall o Fame o he Academy o Human
ii
Resou ce De elopmen , USA, and has won nume ous awa ds o publica ion and jou nal edi ing.
Ana Dias
Ana Alexand a da Cos a Dias has a PhD in Heal h Sciences and Technologies om he Uni e si y
o A ei o (2015), a Mas e s in Inno a ion and Knowledge Managemen om he Uni e si y o A ei o
(2005) and a deg ee in Managemen om he Ins i u e o Supe io , Financial and Fiscal S udies (1998).
She has augh a he Uni e si y o A ei o since 2005 and is cu en ly an Assis an P o esso in he
Depa men o Economics, Managemen , Indus ial Enginee ing and Tou ism (DEGEIT) a UA. She
has been eaching he ollowing subjec s: Models and Business P ocesses, O ganiza ional Beha iou
and O ganiza ional and Social Heal h S uc u es.
He a eas o in e es ocus on o ganiza ional models o heal h ca e p o ision and wo kﬂow
managemen wi h applica ions in he heal h ca e sec o and heal h policy.
She has pa icipa ed in some UA esea ch p ojec s in collabo a ion wi h he social sec o
and he heal h sec o , and she is au ho and co-au ho o scien iﬁc a icles published in na ional
and in e na ional jou nals and has se e al publica ions in na ional and in e na ional con e ence
p oceedings.
She also coope a es as a esea che wi h he esea ch uni on Go e nance, Compe i i eness and
Public Policies (GOVCOPP).
iii
P e ace
In 2020, he wo ld was shaken by a e y unexpec ed de elopmen , an unseen i us which
could kill millions and sp ead wi hou con ol. To educe he impac o he pandemic and be o e
he accine was c ea ed, lockdown and o he sa e y measu es we e implemen ed. In his con ex ,
he socio-economic bu den o he disease was, in ou opinion, a majo issue because we always
conside ed ha COVID-19 would ha e a ha d impac on human beings and ha ha impac would
be he mos p ominen e ec o he pandemic. In consequence, when designing his Special Issue, we
hoped o ecei e pape s wi h ” ales om he ﬁeld” ha would desc ibe he men ioned socio-economic
bu den. The e o e, i was deeply ewa ding o ecei e so many con ibu ions o e y good quali y
ha ended up composing he Special Issue ha is ep in ed he e.
This ep in includes he 11 pape s ha made he Special Issue on he socio-economic bu den o
he disease ega ding he COVID-19 pandemic, published in he Heal hca e jou nal in 2022.
These 11 pape s p o ide a unique se o eﬂec ions ega ding he pandemic and i s consequences
and should be ead by e e ybody in e es ed in he opic.
We since ely hank all he au ho s and e iewe s o he wo k hey p oduced and we
cong a ula e hem o hei success. We belie e ha his ep in o he Special Issue con ibu es o
he unde s anding o he majo consequences o COVID-19 in socie y. C ucially, he ep in includes
pape s on global pe spec i es bu also na ional cases and also sec o -speciﬁc cases. Finally, we hope
he legacy o his olume will be long-las ing and ha he pape s i con ains will be quo ed and ci ed
o many yea s o come.
Edua do Tom´e, Thomas Ga a an, and Ana Dias
Edi o s
ix
Heal hca e 2022,10, 324
4. Me hods and Resul s
This s udy adop ed a spa ial-based and machine lea ning eg ession me hod o analyze
he co ela ion be ween COVID-19 cases, dea hs, and independen a iables. The spa ial
me hod was applied o analyze he co ela ion and o p esen i isually on maps wi h
a ia ion o co ela ion deg ee. ML eg ession model is a s ong ool ha could be used
o di e en opics and pu poses, and he cause and analysis is one o hem. Mo eo e ,
applying se e al models o compa e esul s is impo an o ﬁnd he mos sui able model
o his s udy and documen i . In his s udy, he au ho s used A cGIS-A cMap so wa e
e sion 10.3 o GIS analysis and Jupi e so wa e o apply he eg ession analysis. The
me hod (Figu e 2) applied used GIS ools o spa ial and Sci-Ki Lea n so wa e lib a ies o
machine lea ning eg ession, espec i ely. The GIS eg ession me hods applied ou models:
he sca e plo ma ix g aph, spa ial au oco ela ion (Mo an’s I), o dina y leas squa es
(OLS), and he geog aphically weigh ed eg ession. The ML eg ession me hod applied ou
models, and hey a e linea mul iou pu eg ession, K-nea es neighbo s o mul iou pu
eg ession, andom o es o mul iou pu eg ession, and suppo ec o eg ession. These
models we e applied o analyze he co ela ion be ween dependen (COVID-19 cases and
dea hs) and independen a iables (med-income, po e y a e, popula ion densi y, high
blood p essu e, high choles e ol, obesi y, numbe o heal hy ood ou le s, and numbe o
heal hy ood ou le s).
Figu e 2. Me hodology g aph.
4.1. GIS Me hods
These maps in Figu es 3 and 4 p esen he COVID-19 cases and dea hs. In Figu e 3,
highe numbe s o cases a e p esen ed in da k blue colo . The lowes COVID-19 in ec ions
a e in he down own o G eensbo o, whe e i has ewe esiden ial homes han businesses,
and he highes a e loca ed ou side o G eensbo o in Summe ﬁeld, Gibson ille, Sedalia,
Bu ling on, and Pleasan Ga den. In Figu e 4, he highes numbe s o dea hs a e anging
be ween 22 and 33 pe each census ac , displayed in blue colo , and he lowes numbe s
o dea hs a e gi en 0 o 3 pe each census ac in yellow colo . The COVID-19 dea hs low
numbe s a e epo ed in G eensbo o and he high mo ali y epo ed ou o he ci y. An
obse a ion om his dis ibu ion could be abou people’s educa ion and he mask en o ce-
men in la ge s o es o o ﬁces. A e ha , sca e plo ma ix g aph in Figu e 5 p esen s he
in e ac ion be ween COVID-19 cases and independen a iables. The g aph illus a es some
posi i e and nega i e co ela ions and no co ela ion. Posi i e co ela ions include obesi y
wi h po e y and high blood p essu e. Nega i e co ela ion is p esen ed be ween obesi y
and med-income a iables. Howe e , he e is no appa en s ong co ela ion obse ed
be ween COVID-19 cases and o he a iables h ough his sca e ma ix isualiza ion.
6

Heal hca e 2022,10, 324
Figu e 3. COVID-19 cases in Guil o d Coun y.
Figu e 4. COVID-19 dea hs dis ibu ion.
7
Heal hca e 2022,10, 324
Figu e 5. Sca e plo ma ix g aph using cases as dependen a iable.
The sca e plo ma ix g aph is also applied o COVID-19 dea hs as a dependen
a iable. The g aph (Figu e 6) also p esen s no co ela ion be ween COVID-19 dea hs
and a iables. Nega i e co ela ions a e p esen ed be ween med-income and po e y
and obesi y.
Figu e 6. Sca e plo ma ix g aph using dea hs as dependen a iable.
8
Heal hca e 2022,10, 324
A e ha , we applied he spa ial au oco ela ion (Mo an’s I) o ﬁnd he clus e o cases
and dea hs on some census ac s. The spa ial au oco ela ion is applied by his equa ion:
I=n
S0
∑n
i=1∑n
j=1Wi.jZiZj
∑n
i=1Z2
i
(1)
In Equa ion (1)
Zi
is he de ia ion o an a ibu e o ea u e
i
om i s mean (
Xi−X
).
The
Wi
.
j
is he spa ial weigh be ween ea u e Iand
j
, and
n
is equal o he o al numbe
o ea u es. The
S0
is he agg ega e o all spa ial weigh . A e applying he equa ion,
esul s a e p esen ed in Figu es 7 and 8. Figu e 7 illus a es ha COVID-19 cases a e
signiﬁcan ly clus e ed in Guil o d Coun y, which means he e is high dependency o ou pu
and independen inpu a iables.
Figu e 7. Spa ial au oco ela ion o COVID-19 cases.
Figu e 8. Spa ial au oco ela ion o COVID-19 dea hs.
9
Heal hca e 2022,10, 324
In Figu e 8, he spa ial au oco ela ion concluded ha he clus e o COVID-19 dea hs
is a esul o andom chance, which encou ages he in es iga ion u he on di e en
a iables. The Mo an’s summa y o COVID-19 cases and dea hs by he Mo an’s I spa ial
au oco ela ion is in Table 1 below.
Table 1. OLS esul s o COVID-19 cases and dea hs.
Measu es COVID-19 Cases COVID-19 Dea hs
Mo an’s Index 0.118617 0.005965
Expec ed Index −0.009259 −0.009259
Va iance 0.000575 0.000551
Z-sco e 5.3314423 6.48788
p- alue 0.000000 0.516475
Nex , local Mo an’s was applied based on his o mula:
Ii=χi−X
S2
i
∑n
j−1, j=iwi.j(xj−X)(2)
In Equa ion (2),
n
is he o al numbe o ea u es, and
χi
is he a ibu e o ea u e
i
.
Mo eo e ,
wi.j
is he spa ial weigh be ween ea u e
i
and
j
. The ou pu o his equa ion
is p esen ed in Figu es 9 and 10. Figu e 9, he local Mo an’s on COVID-19 cases, p esen s
ac s wi h high case numbe s and i s co ela ion wi h a high numbe and pe cen age o
a iables in he sou h o G eensbo o and eas o Guil o d Coun y. The pink pa ch ep esen s
high cases o COVID-19 wi h an inc ease in a iables. The ed pa ch ep esen s high cases
and low a iables co ela ion. The blue pa ch illus a es ac wi h low cases numbe wi h
low a iables in G eensbo o down own. In Figu e 10, he local Mo an’s on COVID-19
dea hs is p esen ed wi h he co ela ion o a iables in each ac . The ed pa ch ep esen s
high mo ali y wi h low co ela ion wi h a iables, and he pink pa ch ep esen s high
mo ali y numbe wi h high a iables in he no h o G eensbo o.
Figu e 9. The local Mo an’s on COVID-19 cases in Guil o d Coun y.
10
Heal hca e 2022,10, 324
Figu e 10. The local Mo an’s on COVID-19 dea hs in Guil o d Coun y.
Then, OLS was applied o examine dependen and independen a iables. OLS is a
linea eg ession o pe o m a p edic ion o de ec ela ionship be ween dependen and
independen a iables. We examine COVID-19 cases as a dependen a iable wi h all
independen a iables. This OLS model uses he equa ion below:
Y=β0+β1X1+β2X2+βnXn+
Ɛ
(3)
whe e Y is he dependen a iables,
β
is coe ﬁcien s, X is explana o y o independen
a iables, and
Ɛ
is andom e o . In Figu e 11, ed pa ches ep esen a eas wi h highe
COVID-19 cases han he model p edic ed, and he blue shaded census ac s illus a e
a eas wi h lowe COVID-19 cases han he model expec ed. In his model, he mul iple R
squa e was 0.358946, and he adjus ed R-squa e was 0.307662. The Akaike’s in o ma ion
c i e ion (AICc) was 1412.247528. The join F-s a is ic was 0.000000, which was a signiﬁcan
esul . The Ja que–Be a s a is ic [g] was 1.511785, which indica es ha he independen
a iables ha e an inﬂuence on he dependen a iable. The join Wald s a is ic [e] was
signiﬁcan and compu ed as 0.000000. The Keonke (BP) s a is ics, which de e mine i
he independen a iables ha e a consis en ela ionship o he dependen a iable, was
0.009854, also signiﬁcan , bu he ela ionship is no consis en .
In Figu e 12, ed pa ches ep esen a eas wi h highe COVID-19 dea hs han he model
p edic ed, and he blue shaded illus a es a eas wi h lowe COVID-19 dea hs han he
model p edic ed. In his model, he mul iple R squa e was 0.159614, and he adjus ed
R-squa e was 0.092383. The Akaike’s in o ma ion c i e ion (AICc) was 685.908921. Join
F-s a is ic was 0.021994, which was a signiﬁcan esul . The join Wald s a is ic [e] was
0.000000 as a signiﬁcan esul . The Keonke (BP) s a is ics de e mine i he independen
a iables ha e a consis en ela ionship o he dependen a iable, and i was 0.388493,
which was no signiﬁcan . The Ja que–Be a s a is ic [g] was 0.000000, which is signiﬁcan
and means he model is biased and needs u he in es iga ion.
11

Heal hca e 2022,10, 324
Figu e 11. OLS on COVID-19 cases in Guil o d Coun y.
Figu e 12. OLS on COVID-19 dea hs in Guil o d Coun y.
Based on he independen a iables’ coe ﬁcien o he OLS, a iables wi h highe
coe ﬁcien s han 7.5 will be applied in he GWR. These a iables a e high choles e ol, high
blood p essu e, and heal hy ood ou le s. In Figu es 13 and 14 GWRs we e applied on
COVID-19 cases and dea hs o isualize he co ela ion wi h independen a iables by
applying his equa ion:
y=B0+B1x+E(4)
12
Heal hca e 2022,10, 324
Figu e 13. Geog aphically weigh ed eg ession on COVID-19 cases.
Figu e 14. Geog aphically weigh ed eg ession on COVID-19 dea hs.
In his equa ion abo e, he coe ﬁcien
B1
illus a es he inc ease in y because o
one -uni
inc ease in x. This map shows less ac wi h high co ela ion and mo e wi h
medium co ela ion. In Figu e 13, he map p esen s he co ela ion be ween he dependen
and independen a iables. Red pa ches, which ep esen high co ela ion, a e in eas o
Gil o d Coun y in he ac s 012803, 015300, and 017200. In Figu e 14, he map p esen s
he co ela ion o COVID-19 dea hs wi h a iables (high choles e ol, high blood p essu e,
13
Heal hca e 2022,10, 324
and heal h ood ou le s) and p esen s co ela ion deg ees in colo shades. The highes
co ela ion o COVID-19 dea hs wi h he a iables is p esen ed on he ac s 015703, 012604,
and 013700.
4.2. ML Reg ession Resul s and Discussion
This s udy adop ed machine lea ning echniques o in es iga e he co ela ion by
applying bo h linea and nonlinea eg ession models. Linea , mul i-ou pu linea , andom
o es , and K-nea es neighbo hood eg ession models we e applied o in es iga e he da a.
All models in es iga e all a iables a he same ime, bu linea eg ession in es iga es
single ou pu a a ime. These ou models we e applied o e alua e hei esul s. These
models a e p edic ing he alues o he dependen a iables, such as COVID-19 cases and
COVID-19 dea hs, wi h he co ela ion o independen a iables o med-income, po e y
a e, popula ion densi y, numbe o heal hy ood ou le s, and numbe o un-heal hy ood
ou le s. The da ase was di ided in o 80% aining and 20% es ing o mul iou pu model
de elopmen . The aining se con ained eigh y-se en (87) obse a ions and wen y- wo
(22) obse a ions in he es ing se , and wo di e en me ics: oo mean squa e (RMS) and
R-squa ed (R
2
), which we e used o e alua e he models de eloped. The implemen a ion
o mul iou pu and mul iple linea eg ession models we e done wi h he Sklea n package
in Py hon and MATLAB 2020a, espec i ely. The de aul pa ame e s o he mul iou pu
eg ession models we e used in Table 2.
Table 2. Reg ession models’ pa ame e s.
Model Pa ame e s
Linea Reg ession Model copy_X = T ue,ﬁ _in e cep = T ue,n_jobs = None,no malize = False.
Random Fo es Reg ession Model
boo s ap = T ue,ccp_alpha = 0.0,c i ion = ‘mse’,max_dep h =
None,max_ ea u es = ‘a o’,max_lea _nodes = None,max_saples =
None,min_impu i y_dec ease = 0.0,min_imp i y_spli =
None,min_samples_lea = 1,min_samples_spli = 2,min_weigh _ ac ion_lea =
0.0,n_es im o s = 100,n_jobs = None,oob_sco e = False, andom_s a e =
None, e bose = 0, wa m_s a = False)
K-Nea es Neighbo Reg ession Model lgo i hm’:’au o’,’lea _size’:30,’me ic’:’minkowski’,’me ic_pa ams’: None,
‘n_jobs’: None,’n_neighbo s’: 5, ‘p’: 2, ‘weigh s’: ‘uni o m’
The equa ion below is de i ed in he linea eg ession model. In he equa ion, coe ﬁ-
cien s o a iables we e compu ed based on he linea eg ession model.
Y = 0.53 + 0.194 ×1−0.251X2+ 0.887X3−0.915X4−0.0996X5+ 0.315X6−0.026X7(5)
The deg ee o linea associa ion be ween all a iables is compu ed by he Pea son
co ela ion coe ﬁcien (R
2
)-sco es in he co ela ion ma ix hea map o ma in Figu e 15. The
esul s could be ead in h ee di ec ions: R alues close o 1 show a posi i e ela ionship,
and R alues close o
−
1 illus a e nega i e ela ionships, bu esul s close o ze o ha e no
linea ela ionships. I can be obse ed in he hea map (Figu e 13) ha he e is a posi i e
co ela ion be ween obesi y and po e y (R
2
= 0.74). The e is a high posi i e co ela ion
be ween high choles e ol and high blood p essu e (R
2
= 0.82). Fu he mo e, he e is a
posi i e co ela ion be ween obesi y and high blood p essu e (R
2
= 0.77). Mo eo e , he e is
a s ong nega i e co ela ion be ween obesi y and med-income (R
2
=
−
0.7), and a nega i e
co ela ion be ween income and po e y (R
2
=
−
0.75). The e is no co ela ion be ween
COVID-19 cases and heal h issues (obesi y, high choles e ol, and high blood p essu e).
Mo eo e , he e is no co ela ion be ween unheal hy ood ou le s, heal hy ood ou le s, and
heal h issues.
14
Heal hca e 2022,10, 324
Figu e 15. Co ela ion ma ix wi h hea map.
F om he ables’ esul s below (Tables 3 and 4), he au ho s applied and compa ed he
eg ession models esul s. The COVID-19 cases as a dependen a iable ha e he highes
alue o R
2
-sco e as 45% by he applica ion o linea eg ession o mul iou pu eg ession
model, and COVID-19 dea hs had a highe alue o 60% by he applica ion o suppo ec o
eg ession model. The high co ela ion R
2
-sco es o COVID-19 dea hs and a iables we e
also p esen ed by he GIS spa ial au oco ela ion as clus e ed dis ibu ion in Figu e 7. These
eg ession models’ esul s indica e ha independen a iables (med-income, po e y a e,
popula ion densi y, numbe o heal hy ood ou le s, and numbe o unheal hy ood ou le s)
ha e mo e inﬂuence on he dependen a iable COVID-19 dea hs han COVID cases.
Table 3. R-squa e alue o eg ession models.
Roo Mean Squa e E o
Models CVID-19 Cases COVID-19 Dea hs
Linea eg ession o mul iou pu Reg ession 0.146 0.141
K-nea es neighbo s o mul iou pu eg ession 0.208 0.147
Random o es o mul iou pu eg ession 0.186 0.175
Suppo Vec o Reg ession 0.168 0.127
15
Heal hca e 2022,10, 315
will p omo e equali y, s imula e egional ou pu , diminish egional unemploymen , and in-
c ease income le els. In es men s in o less de eloped egions sugges highe mul iplica i e
e ec s, sugges ing he use o in es men in o egional heal hca e sec o s as a ool o equal
egional de elopmen .
Al hough heal hca e spending has been g owing o decades in a la ge numbe o
coun ies, he e we e a emp s o cu he cos s, especially in imes o public ﬁnance con-
s ain s. Empi ical da a and he li e a u e gi e g ounds o belie e his s a egy does no
b ing he desi ed esul in ei he he economic pe spec i e, as aus e i y measu es do no
p omo e bu a he ha m he eco e y (Da as e al. [
14
]), no in he heal h ou comes, as
he a oidable mo ali y can be a ec ed. A s udy by A cà e al. [
28
] e eals ha , e en in
coun ies wi h ela i ely low a oidable mo ali y, spending cu s in heal hca e can hu
su i al. Fu he mo e, he p ocyclicali y ma e s, as educing p ocyclicali y o go e nmen
heal h expendi u e by keeping hem in bad imes may gene a e subs an ial heal h gains
(Liang and Tussing [29]).
The li e a u e ex ensi ely explo es economic e ec s o he pandemic along wi h he
policy measu es o educe hem and he damage o he na ional and global economy. These
measu es a ise om mone a y, mac op uden ial, and ﬁscal policies. Applied policies in-
clude elie measu es, eco e y policies, and in e na ional coo dina ion measu es and a e
s a ed o educe he consequences independen ly o as a combined mix o measu es [
19
].
Howe e , while such a esea ch app oach explo es policy op ions o ac agains he con-
sequences o an economic c isis caused by he pandemic, ou app oach is inno a i e in
mo ing he pe spec i e o he op ions o economic policy o educe con ibu ing ac o s o
he se e i y o he pandemic ou come. The p esen s udy is hus o iginal in he ollowing
ways. While he economic li e a u e o en akes he pe spec i e o empi ically explo ing
an indi idual de e minan o some de e minan s which a e ex-an e, selec ed based on
heo e ical g ounds and he impac on he heal h ou comes du ing a speciﬁed ime ame,
we ake an inno a i e poin o iew. We awai o iden i y a eas whe e an impac on he
heal h ou comes in he case o he COVID-19 pandemic o igina ed and can be a ec ed by
economic policy measu es in he sho - o long- e m pe spec i e o enhance eliance o
possible u u e heal h c isis.
The pape is o ganized as ollows. A e highligh ing he ele an economic cha ac e -
is ics and explo ing g ounds o economic eco e y in he ﬁ s sec ion, we p esen he da a
sou ces and me hods used in he s udy. Nex , Sec ion 3 gi es echnical esul s and hei
in e p e a ion ega ding he esea ch ques ion. Finally, Sec ions 4 and 5 comple e wi h he
discussion and conclusions, espec i ely.
2. Ma e ials and Me hods
Al hough he COVID-19 epidemic is no ye o e , al eady a lo o da a is made a ail-
able by s a is ical o ﬁces, in e na ional o ganiza ions, na ional go e nmen s and hei
public heal h ins i u es, and many o he o ganiza ions. Ini ially, we ha e collec ed 171
da a a iables o 197 coun ies, om 2017 o 2020, o ensu e ha , in some mino cases
whe e he mos cu en da a we e no a ailable, he la es possible da a, o an es ima-
ion, we e aken. Collec ed da a conside ed economic, in as uc u e, cul u al, heal h,
and o he a eas. Economic a iables we e ob ained om Wo ld Bank Open Da a (h ps:
//da a.wo ldbank.o g/, accessed on 10 Decembe 2020), IMF’s Wo ld Economic Ou look
Da abase (h ps://www.im .o g/en/Publica ions/WEO/weo-da abase/2020/Oc obe ,
accessed on 10 Decembe 2020), T ading Economics po al (h ps:// adingeconomics.
com/indica o s, accessed on 10 Decembe 2020), and FDI A ac i eness Index websi e
(Ben [
30
], accessed on 10 Decembe 2020) (h p://www. dia ac i eness.com/ anking-
2020/, accessed on 10 Decembe 2020). In as uc u e a iables we e e ched om En-
e da a (h ps://yea book.ene da a.ne /, accessed on 10 Decembe 2020) and ITU (h ps:
//www.i u.in /en/ITU-D/S a is ics/Pages/s a /de aul .aspx, accessed on 10 Decembe
2020), while o he ele an cul u al a iables om Wikipedia, ETH’s KOF (h ps://ko .
e hz.ch/en/ o ecas s-and-indica o s/indica o s/ko -globalisa ion-index.h ml, accessed
on 10 Decembe 2020) (Gygli e al. [
31
] and D ehe [
32
]), and Google Mobili y (GM) web-
22

Heal hca e 2022,10, 315
si e (h ps://www.google.com/co id19/mobili y/, accessed on 10 Decembe 2020). As GM
da a we e epo ed as high equency (daily) da a, basic ans o ma ion o in eg a ion wi h
he low- equency da a (o he s) we e necessa y. Fi s , he a e age alues o GM da a du ing
he ﬁ s co ona- i us ou b eak (1 Ma ch–1 May 2020) and du ing he second ou b eak (las
wo mon hs p io o 6 h Decembe 2020) we e calcula ed. Two ec o s o six ca ego ies
( e ail and ec ea ion, supe ma ke and pha macy, pa ks, public anspo , wo kplaces, and
esiden ial) we e buil in his way.
Nex , he a e age be ween he wo buil ec o s was aken o o m a single, consol-
ida ed, composi e indica o . The e, i was ound ha he e ail and ec ea ion ca ego y
showed as mos ele an he e. Va iables on heal h ou comes we e ob ained om WHO’s
Global Heal h Obse a o y da a eposi o y h ps://apps.who.in /gho/da a/node.main
(accessed on 10 Decembe 2020) and Nex s ain h ps://nex s ain.o g/nco /global (Had-
ﬁeld e al. [
33
], accessed on 10 Decembe 2020). These we e also ca ego ized as high
equency da a (numbe o in ec ed, dead, and eco e ed people and numbe o clade
mu a ions) and we e eco ded a he day o beginning he esea ch, i.e., 10 h Decem-
be . Again, hese equi ed specialized ea men , such ha composi e indica o s we e
buil . The es o he a iables came om a consolida ed web po al, Ou Wo ld in
Da a h ps://ou wo ldinda a.o g/cha s (accessed on 10 Decembe 2020), which holds
da ase s o di e en da a p o ide s. A e building a comple e (consolida ed) da ase as a
combina ion o high and low equency da a, missing da a we e ound such ha cleaning
o da ase was necessa y. Two e sions o educed da ase s we e gene a ed. In he ﬁ s ,
he e we e da a o 78 coun ies wi h 11 a iables al oge he . In he second, by educing
he numbe o coun ies, 13 mo e a iables could be included. The lis o he explana o y
a iables is as ollows and can be di ided in o se e al g oups: i us cha ac e is ics (COVID-
19 cases—cumula i e o al, COVID-19 i us clade 20A, and COVID-19 i us clade 20B),
popula ion cha ac e is ics (sha e o popula ion olde han 65, sha e o he popula ion li ing
in u ban a eas, mean BMI (male and emale)), equali y cha ac e is ics ( emale employmen -
o-popula ion a io and Gini index o consump ion), heal hca e sec o cha ac e is ics (sha e
o public heal hca e sec o and he Heal hca e Access and Quali y Index), na ional economy
cha ac e is ics (GDP pe capi a and PPP, i.e., cons an 2011 in e na ional $, High-Tech expo
(sha e o manu ac u ed expo s), FDI coun y a ac i eness, and sha e o he ag icul u e
sec o ), and cul u al cha ac e is ics (Google mobili y measu es). Addi ionally, as dummy
a iables, we included he wo ld egions. Bo h educed da ase s we e gene a ed o he bes
ex en , comp omising he numbe o a iables and numbe o coun ies o ha e a good mix
o high- and low-income coun ies. Finally, all he a iables we e s anda dized be o e use
in models by sub ac ing he mean and di iding by he s anda d de ia ion.
As he dependen a iable we used da a on he numbe o COVID-19 dea hs om
WHO’s COVID-19 Dashboa d as he a iable indica ing he se e i y o he COVID-19 epi-
demic ou come in an indi idual coun y. All ga he ed da a was p epa ed in p e-p ocessing
s ep (e.g., loga i hmic ans o ma ion) and analyzed in o de o p epa e o es ima ion o
eg ession models. In he ﬁ s wo models, he leas squa es me hod was used. In he hi d
one, he Hube -Whi e-Hinkley es ima o was used. We used so wa e package EViews 10+
(En e p ise Edi ion, 64-bi , IHS Global Inc., I ine, CA, USA, 2018) o he model es ima ion.
A limi a ion o he s udy has o be no ed he e. Al hough we ha e aken uniﬁed da a
sou ces ac oss coun ies, di e en inconsis encies in he me hodology o collec ing da a can
be ound, e.g., numbe o dead due o COVID-19 (as a main sou ce o implica ion) is no
uniquely deﬁned ac oss coun ies. The ull ex en o COVID-19 ou come will be possible o
be e alua ed when all s a is ical da a in ull ange and eliabili y will be a ailable.
3. Resul s
Based on empi ical e idence, we conside ed es ima ions on mul iple eg ession models
o d aw an in eg al amewo k o iden iﬁca ion o a eas, whe e he de e minan s o se e i y
o COVID-19 ou come came om. Al hough he esul s depend on he limi ed selec ion
o coun ies and a iables, bo h loga i hm–linea and linea –linea models sugges ed
easonably-conno a ed connec ions. Mul iple models we e es ima ed ins ead o one, and
23
Heal hca e 2022,10, 315
amewo k comp ises h ee models and uni es he indings al oge he . This is p esen ed in
Figu e 1. We chose he p esen ed h ee models o e o he expe imen al models as hey a
bes me he c i e ia o high explana o y powe , exp essed by high le els o coe icien o
de e mina ion (R-squa ed). Howe e , he abili y o u he imp o e he s udy’s econome ic
quali y was impac ed by ou esea ch aim o including he bigges possible numbe o
coun ies and he wides possible selec ion o he explana o y a iables. Ne e heless,
he inal models exhibi high alues o R-squa ed, especially due o he ac ha we a e
dealing wi h c oss-sec ion and highly he e ogeneous da a.
Model 1 Model 2 Model 3
Co id
19 ou come a iable
LOG(Dea hs -
cumula� e
o al)
Dea hs - cumula� e
o al
Dea hs - cumula� e
o al
De e minan s o he Co id 19 ou come
Coeﬃcien
P ob.
Coeﬃcien
P ob.
Coeﬃcien
P ob.
Sou h Ame ica
-
1.381
***
Regional cha ac e is�cs
No policy measu es
possible
A ica
-
1.856
***
Asia
-
1.894
***
-
0.639
*
-
0.7105
*
Oceania
-
3.360
***
-
2.828
***
-
4.8998
***
Co id 19 Cases - cumula� e o al
0.307
***
Vi us cha ac e is�cs No policy measu es
possible
Co id 19 i us clade _20A
0.024
0.030
0.4856
Co id 19 i us clade _20B
0.250
*
0.240
*
0.6210
***
Sha e o popula�on olde han 65
-
0.587
**
Popula�on
cha ac e is�cs
Long- and mid- e m policy
measu es possible
Sha e o he popula�on li ing in u ban a eas
1.713
***
2.0748
**
Mean BMI (male and emale)
3.872
**
9.9473
***
Female employmen - o-popula�on a�o
-
1.266
***
Equali y cha ac e is�cs
Long-, mid-, and sho - e m
policy measu es possible
Gini index o consump�on
-
1.814
**
-
3.9628
***
Sha e o public heal h ca e sec o
-
0.478
*
-
0.9352
**
Heal h sec o
cha ac e is�cs
Long-, mid-, and sho - e m
policy measu es possible
Heal hca e Access and Quali y Index
-
3.9142
**
GDP pe capi a, PPP (cons an 2011
in e na�onal $)
-
0.393
*
Na�onal economy
cha ac e is�cs
Long-, mid-, and sho - e m
policy measu es possible
High-Tech expo (sha e o manu ac u ed
expo s)
-
0.350
**
-
0.7123
***
FDI coun y a� ac� eness
5.063
***
6.7496
***
Sha e o he ag icul u e sec o
-
0.393
*
Google mobili y measu es
0.451
***
0.4016
***
Cul u al cha ac e is�cs
Sho - e m policy measu es
possible
Cons an
0.101
-
5.472
***
-
11.4865
***
Sample
78
61
61
R-squa ed
0.734
0.664
0.7918
F-s a�s�c
16.538
***
8.794
***
15.2122
***
Me hod
Leas Squa es Leas Squa es
Hube -Whi e-
Hinkley es�ma o
A eas o
possible policy
measu es
Types o
possible policy
measu es
Complexi y
o possible
policy
measu es
Figu e 1. ‘*’ = p- alue lowe han 0.10, ‘**’ = p- alue lowe han 0.05, ‘***’ = p- alue lowe han 0.01.
Economic policy amewo k o de e mining pandemic ou b eak measu es. Sou ce: own calcula ions
and igu e p esen a ion.
In his esea ch, he e was a challenge o he e oscedas ici y. In he modelling phase, we
con olled o he he e oscedas ici y by di e en app oaches e lec ed in he h ee models.
In he i s , we chose o use he loga i hmic alue o he dependen a iable. In he hi d,
we ook ano he app oach, namely, a he e oscedas ici y obus es ima o : Hube –Whi e–
Hinkley es ima o . Fo a benchma k, we did no apply any adjus men s in he second
model due o he he e oscedas ici y.
When in e p e ing he esul s, ano he ac should be aken in o accoun , namely
he possible p esence o mul icollinea i y. In he ini ial modelling s ep, mul icollinea i y has
impac ed he selec ion o explana o y a iables se e ely. A e he selec ion, we empi ically
ound ha a possible h ea o mul icollinea i y was s ill indica ed in he model. Namely,
some o he eg ession coe icien s exposed he signs (conno a ions, i.e.,
−
/+) opposi e as
expec ed, which we in e p e ed exclusi ely as a consequence o mul icollinea i y. S ill, we
ollowed a common econome ic ule ha a mul icollinea i y is no a eason o omi ing
he model.
The e we e dummy a iables included in he models o egions ha s a is ically sig-
ni ican ly de ia ed om he global a e age. We belie e his is due o he huge di e ences in
he ini ial posi ion a he beginning o he epidemic in indi idual coun ies. Howe e , when
conside ing he obus es ima o , he only signi ican esul s emain he dummies o Asia
and Oceania, whe e e y es ic i e measu es agains he sp ead o he i us we e applied.
The esul s on he es ima ed econome ic models e eal some in e es ing indings.
Among con ibu ing ac o s o a mo e se e e epidemic ou come, highe popula ion mobili y,
a highe le el o he popula ion li ing in u ban a eas, a weake physical condi ion o he
popula ion, and he openness o he economy all ea u ed. On he o he hand, a posi i e
impac came om a highe sha e o he p ima y economic sec o in he ecosys em s uc u e
(ag icul u e) and high economic de elopmen measu ed as High-Tech expo . Addi ionally,
24
Heal hca e 2022,10, 315
impac came om a highe sha e o he p ima y economic sec o in he ecosys em s uc u e
(ag icul u e) and high economic de elopmen measu ed as High-Tech expo . Addi ionally,
he impo ance o public heal hca e was e ealed, as be e heal hca e access and quali y
no ably con ibu ed o a mo e a ou able epidemic ou come.
The esul s sugges he e a e mul iple a eas which de e mined he se e i y o he
COVID-19 ou come in indi idual coun ies:
• egional cha ac e is ics;
• i us cha ac e is ics;
• popula ion cha ac e is ics;
• equali y cha ac e is ics;
• heal hca e sec o cha ac e is ics;
• na ional economy cha ac e is ics;
• cul u al cha ac e is ics.
When examining he a eas closely, he o e all analysis o all h ee models sugges s
ha he e a e h ee g oups o ac o s which inﬂuence he ou come o he pandemic in
indi idual coun ies. In ega ds o he economic policy, hese g oups di e and can be
lis ed as ollows:
• a eas whe e ac o s canno be inﬂuenced by economic policy measu es;
• a eas whe e ac o s can be inﬂuenced by long- and mid- e m policy measu es;
•
a eas whe e ac o s can also be inﬂuenced wi h sho - e m policy measu es and p omp
esul s a e possible.
The analysis o he amewo k e eals ha economic policy measu es canno inﬂuence
he egional cha ac e is ics, e.g., whe e he indi idual coun y is placed, as well as he
i us cha ac e is ics, e.g., i us clade p esen in he pa icula coun y. The o he wo
g oups o ac o s a e ele an o he economic policy, as hey migh be inﬂuenced by long,
mid-, and sho - e m policy measu es. The a ea o popula ion cha ac e is ics could be
add essed wi h mid- and long- e m measu es, and could be di ec ed o he popula ion
s uc u e, anging om li ing condi ions such as u baniza ion up o ageing s uc u e o
physical cha ac e is ics o he popula ion. The g oup o measu es, likely o be less complex
han hose p e ious, would be long-, mid-, and sho - e m policy measu es and would
aim o a ou ably enhance he equali y cha ac e is ics o he socie y. The unde s anding
o equali y, in his sense, is b oad and includes he gende impac , he labou ma ke
condi ions, and he dis ibu ion o weal h, also on he egional le el.
The nex a ea o possible economic policy measu es would be unde aken aiming a
changes o he heal hca e sec o cha ac e is ics. These can be impac ed wi h combina ion
o long-, mid-, and sho - e m measu es, he e o e i also includes s uc u al cha ac e is ics
o he sec o , including he capaci y, quali y, and accessibili y o he se ices. The a ea o
cha ac e is ics o he heal hca e sec o includes he s uc u e acco ding o he public and
p i a e sha e o he heal hca e sec o . The esul s a e in a ou o a la ge sha e o he public
heal hca e sec o .
Ou esul s also indica e ha he cha ac e is ics o na ional economy had an impac
on he se e i y o he pandemic ou come. By economic cha ac e is ics, no only he le el
o economic de elopmen measu ed by e.g., GDP pe capi a is mean , bu he s uc u e o
he economy, namely he sec o al s uc u e, is encoun e ed. The le el o inno a ion and
s uc u al changes will be a he o e on o his a ea o economic policy measu es.
Fu he mo e, sho - e m policy measu es could inﬂuence he a ea o cul u al cha ac-
e is ics, among which he mobili y o he popula ion is limi ed. The complexi y o measu e
will g adually inc ease. The less complex measu es will be applied a he a ea o popula ion
cha ac e is ics, while he mos complex measu es a e expec ed o be applied a he a ea o
na ional economy cha ac e is ics and he cul u al cha ac e is ics.
Based on empi ical ﬁndings, we p opose a mix o possible economic policy measu es
di ec ly o indi ec ly linked o he heal hca e sec o . This includes p omo ing public heal h-
ca e, ensu ing c isis capaci ies, and access o quali y heal hca e. On he o he hand, s a e
and obliga o y heal h insu ance p emiums should also accoun o indi iduals’ decisions,
25
Heal hca e 2022,10, 315
esul ing in highe heal hca e cos s, e.g., non- accina ion once a accine is a ailable. Al e -
na i ely, pa icipa ion in heal hca e cos s o non- accina ed could be applied and used o
ﬁnance scaling-up he capaci ies. To encou age a esilien economy o he u u e, economic
policy mus implemen policy measu es, based on empi ical ﬁndings on cha ac e is ics o
economic s uc u es and mul iplica i e e ec s as well as ac ual lessons lea ned om he
economic consequences o COVID. Fu he mo e, i has been a gued ha s anda d ﬁscal
s imulus migh be less e ec i e han no mally expec ed due o mu ed Keynesian mul iplie
eedback (Gue ie i e al. [
10
]). Addi ionally, as indica ed in he li e a u e (Bekö e al. [
15
]),
he impac o he heal hca e sec o seems o emain s able h oughou he business cycle,
which sugges s he p edic abili y o economic measu es.
In he end, economic eco e y is cos ly. Ins ead o bu dening u u e gene a ions
due o highe public deb , ﬁnancing sou ces should be a he cos o indi iduals who
beha e oppo unis ically in he epidemic c isis. S a e so e eign y includes ﬁscal measu es;
he e o e, ﬁnding hese addi ional sou ces in a o m o a COVID-19 ax could be jus iﬁed.
4. Discussion
As wi h any s udy, he limi a ions ha e o be conside ed o p ope in e p e a ion o
he esul s. In his s udy, limi a ions a ise om wo pe spec i es: he da a and he me hods.
Al hough we ha e aken uniﬁed da a sou ces ac oss coun ies, we ound inconsis encies in
hei da a collec ion app oaches, e.g., numbe o dea hs due o COVID-19 is no uniquely
deﬁned ac oss coun ies. Fu he , he da a a ailabili y was limi ed in he sense ha o
an indi idual a iable o some coun ies he e we e missing alues. Consequen ly, i has
led o he ade-o be ween a la ge numbe o a iables o a la ge numbe o included
coun ies. The esul s a e hus impac ed by he choice we made in his pe spec i e and
migh di e om models, whe e we would ei he include ewe explana o y a iables bu
e en mo e coun ies o con a y, mo e explana o y a iables, and ewe coun ies. Fu he ,
ega ding he s udy design, s anda d es ing o policy impac (e.g., ea men e ec models,
bu also G ange causali y es ) was acco ding o he na u e, quali y, and a ailabili y o
da a no possible o apply. Addi ionally, because he pandemic and he applied measu es
ha e no ye come o an end, o he econome ic app oaches as wha we wen o did no
seem easonable in ou case. Again, we ied o make he s udy as b oad as possible (in he
numbe o coun ies included and in he ange o a iables included), which also impac ed
he possibili ies o applied econome ic app oaches.
The ob ained scien iﬁc implica ions hus a e based on a s a ing pe iod o he COVID-
19 pandemic. La e , i will be possible o e alua e he ull ex en o he dependencies
analysed he e in ela ion o COVID-19, once all s a is ical da a in ull ange and eliabili y
is be a ailable.
The s udy gi es se e al scien iﬁc implica ions. We ound ha mul iple ac o s, which
de e mined he se e i y o he COVID-19 ou come in indi idual coun ies, a ise om
egional, i us, popula ion, equali y, heal hca e sec o , na ional economy, and cul u al
cha ac e is ics.
Along wi h he scien iﬁc implica ions p esen ed in de ail in he esul s sec ion, ano he
impo an ﬁnding was e ealed by his s udy, namely he ele ance o high- equency da a.
In ou s udy, we used Google mobili y da a as one explana o y a iable, bu many mo e
could be ele an in he u u e. High- equency da a, in gene al, eme ged as a esul o he
use o mode n in o ma ion echnologies. Howe e , wo aspec s o hei applicabili y in
science ha e o be gi en a en ion: ﬁ s , app op ia e me hodological app oaches capable o
dealing wi h such da a, and secondly, he a ailabili y o he da a o he scien iﬁc communi y.
Nex , we u n o he economic policy amewo k, which is se ing as an iden iﬁca ion
ma ix o policy implica ions. We iden iﬁed se e al a eas ha could be ele an o
he se e i y o he epidemic ou come. This sec ion discusses se e al ideas ha sugges
economic policy measu es o impac he se e i y o he epidemic ou come a ou ably.
Ou esul s sugges ha na ional economy cha ac e is ics ma e ; hus, we discuss he
policy measu es which would add ess hem. The GDP pe capi a and high- ech expo
could be inﬂuenced. Financial da a show ha he heal hca e sec o s’ s ocks ou pe o med
26
Heal hca e 2022,10, 315
mos o he s. The esea ch and de elopmen in he heal hca e sec o indus y p omo es
a high le el o inno a ion which no only con ibu es o he a o dable heal hca e, bu
p omo es economic de elopmen wi h high alue-added and c ea es jobs o highly skilled
p o essionals. Encou aging in es men s in inno a i e indus ies (heal hca e, pha maceu i-
cal, bio ech, and associa ed indus ies) could hus be a good way o inﬂuence he a iables
which a e ound in he g oup “na ional economy cha ac e is ics” in ou amewo k.
Nex , we a gue ha pos COVID-19 in es men s should encou age R&D in a iﬁcial
in elligence (AI). Inno a ion and ans o ma ion accele a e economic g ow h and p omo e
esilien economic sys ems. AI can al eady be applied as he ﬁ s s age in diagnosing less
se e e cases, he eby eleasing capaci ies (AbuShaban [
2
]). In es ing in AI in he heal hca e
sec o will ha e huge spill o e e ec s, as his means in es men in o AI p o essionals,
companies de eloping AI solu ions, and implemen a ion o hese solu ions in o he sec o s,
making he economy u u e- eady. P omo ing R&D in AI and AI usage in heal hca e could
ha e a a ou able impac on he a iables in he g oups “na ional economy cha ac e is ics”
as well as “heal h sec o cha ac e is ics”. Addi ionally, AI can be seen as a con enien ool
o s ipula ion o a heal hy li es yle (in sma wa ches, senso s, and wea ables), which im-
po an ly lowe s COVID-19 se e i y (we no iced a signiﬁcan connec ion be ween physical
condi ion measu ed by BMI and cumula i e o al).
We u he discuss he measu es aiming o change he cha ac e is ics o he heal h-
ca e sec o , especially due o he high ele ancy o he eg ession a iable “Heal hca e
Access and Quali y Index” (
−
3.9142 **), as indica ed in he hi d model o he a iable.
Addi ionally, he amewo k om his s udy indica es ha he p i a e–public heal hca e
ma e s. As he heal hca e sec o mus be pa o he c i ical in as uc u e, he go e nmen
and he p i a e sec o should es ablish a ela ionship be ween each o he o encou age he
necessa y coope a ion (see also AbuShaban [
2
]). Ne wo ks o egional p o ide s a e mo e
c i ical o communi y eco e y han cen es.
Public heal hca e p o ide s a e mo e sui able o p o ide su ﬁcien backup capaci ies in
a eas which a e no p oﬁ able. I public heal hca e p o ide s ope a e in p oﬁ able heal hca e
se ices, p oﬁ s can be used o co e ing losses om ope a ing in non-p oﬁ able se ices.
Fo example, ese ing and main aining capaci ies o na ional medical eme gencies is
cos ly and does no gain p oﬁ s.
T ans o ma ion o heal hca e sys ems wi h mo e ﬂexibili y can con ibu e o p o ide
access o quali y heal hca e. Bo h ﬂexibili y in physical capaci ies (AbuShaban [
2
]) and
medical s a ﬂexibili y (Fe ei a e al. [
34
], Casha and Casha [
35
]) should hus be add essed.
The heal hca e sec o o many coun ies is su e ing om medical s u sho ages esul -
ing om emig a ion o medical p o essionals (Fe ei a e al. [
34
], Casha and Casha [
35
]). We
a gue ha he e is he need o design policy measu es ha mi iga e he in en ion o heal h-
ca e p o essionals o emig a e. Tempo a y deﬁci s on he labou ma ke s can be sol ed by
encou aging sho - e m medical s a mobili y. Long- e m sho ages should be add essed
by economic policy measu es. Howe e , one mus no ice ha mobili ies in gene al a e no
app ecia ed, as he “Google mobili y measu es” exposes posi i e eg ession coe ﬁcien s.
Addi ionally, we sugges econside ing “s a e aid” in indus ies ha nega i ely a ec
heal h and en i onmen in any economic policy ac ion. The e o e, capi al injec ion measu es
should be conside ed in indus ies acco ding o economic, en i onmen al, and heal h
c i e ia. This would ha e long- e m e ec s on heal h and en i onmen and would make
economies mo e esilien o u u e dis up ions while also con ibu ing o equi y.
5. Conclusions
In his s udy, we suppo he hesis ha inno a i e measu es o economic policy
should be applied in he a e -COVID-19 pe iod. These measu es should di e om
adi ional ones, be applied in ad ance o an epidemic, and hus o suppo economic
and social ecosys ems o become mo e esis an o cu en and u u e epidemic c ises.
Many o he p oposed measu es di ec ly o indi ec ly conce n he heal hca e sys ems and
heal hca e sec o , aiming o impac i s cha ac e is ics, such as public- s-p i a e heal hca e
o he access and quali y o he heal hca e p o ided. Economic policy measu es could hus
27

Heal hca e 2022,10, 315
p omo e new echnologies in heal hca e, sec o al s a ﬂexibili y, o ein o ce decen alised
( egional) public heal h se ices p o ide s. A cen al elemen o his s udy, he inno a i e
iden iﬁca ion ma ix, which combines unbiased econome ic esul s wi h emedia ion,
could be popula ed as a unique policy amewo k, ei he o la es pandemic o any simila
ou b eaks in u u e. Howe e , such a policy amewo k is no only o be used o iden i ying
pandemic ou comes, bu also when he ﬁnal da a on he pandemic ou b eak ou comes
become a ailable, o make accu a e and eliable p edic ions o he e ec on indi idual
economic, heal h, and social li e ac o s. In he end, i s applica ion in policy design could
con ibu e o mode n socie ies’ e o s on equali y, human igh s, and social cohesion.
We sugges u he esea ch on his opic. Wi h he passage o ime, he da a on he
longe ime ame o he COVID-19 pandemic pe iod will be a ailable. This would enable
a panel-based econome ic app oach ins ead o a c oss-sec ional one. In doing so, bo h he
ange o included cha ac e is ics o he coun ies and he gene ic changes o he i us could
imp o e he model and e eal new dependencies in he examined coun ies’ cha ac e is ics
o he se e i y o he pandemic. Addi ionally, as we discussed he scien iﬁc po en ial o
high- equency da a, u u e esea ch could include hem in in es iga ions. The la e would
enable he de ailed s udy o in e ac ion be ween high- equency da a a iables and he
gene ic p oﬁle o he i us.
Au ho Con ibu ions:
Concep ualiza ion, T.J.; me hodology, T.J.; so wa e, T.J. and D.F.; alida ion,
T.J. and D.F.; o mal analysis, T.J. and D.F.; esou ces, D.F.; da a cu a ion, D.F.; w i ing—o iginal d a
p epa a ion, V.J.; w i ing— e iew and edi ing, T.J. and V.J.; isualiza ion, T.J.; and supe ision, T.J.
All au ho s ha e ead and ag eed o he published e sion o he manusc ip .
Funding:
The au ho s acknowledge he ﬁnancial suppo om he Slo enian Resea ch Agency
(Resea ch co e unding No. P5-0027).
Ins i u ional Re iew Boa d S a emen : No applicable.
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen :
Publicly a ailable da ase s om mul iple sou ces we e analysed in
his s udy. The da a can be ound he e: [h ps://da a.wo ldbank.o g/, h ps://www.im .o g/en/
Publica ions/WEO/weo-da abase/2020/Oc obe , h ps:// adingeconomics.com/indica o s, h p:
//www. dia ac i eness.com/ anking-2020/, h ps://yea book.ene da a.ne /, h ps://www.i u.
in /en/ITU-D/S a is ics/Pages/s a /de aul .aspx, h ps://ko .e hz.ch/en/ o ecas s-and-indica o s/
indica o s/ko -globalisa ion-index.h ml, h ps://www.google.com/co id19/mobili y/, h ps://
apps.who.in /gho/da a/node.main, h ps://nex s ain.o g/nco /global, h ps://ou wo ldinda a.
o g/cha s], all accessed on 10 Decembe 2020.
Conﬂic s o In e es :
The au ho s decla e no conﬂic o in e es . The unde s had no ole in he design
o he s udy; in he collec ion, analyses, o in e p e a ion o da a; in he w i ing o he manusc ip ,
o in he decision o publish he esul s.
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29
heal hca e
A icle
The Economic and Psychological Impac s o COVID-19
Pandemic on Indian Mig an Wo ke s in he Kingdom o
Saudi A abia
Mohammed A shad Khan 1,*, Md Im an Khan 2, Ashe e Illiyan 2and Maysoon Khojah 1
Ci a ion: Khan, M.A.; Khan, M.I.;
Illiyan, A.; Khojah, M. The Economic
and Psychological Impac s o
COVID-19 Pandemic on Indian
Mig an Wo ke s in he Kingdom o
Saudi A abia. Heal hca e 2021,9, 1152.
h ps://doi.o g/10.3390/
heal hca e9091152
Academic Edi o s: Edua do Tomé,
Thomas Ga a an, Ana Dias and
Ped am Sendi
Recei ed: 21 July 2021
Accep ed: 27 Augus 2021
Published: 3 Sep embe 2021
Publishe ’s No e: MDPI s ays neu al
wi h ega d o ju isdic ional claims in
published maps and ins i u ional a ﬁl-
ia ions.
Copy igh : © 2021 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license (h ps://
c ea i ecommons.o g/licenses/by/
4.0/).
1Accoun ing Depa men , College o Adminis a i e and Financial Sciences, Saudi Elec onic Uni e si y,
Riyadh 11673, Saudi A abia; [email p o ec ed]
2Depa men o Economics, Facul y o Social Sciences, Jamia Millia Islamia (A Cen al Uni e si y),
New Delhi 110025, India; [email p o ec ed] (M.I.K.); [email p o ec ed] (A.I.)
*Co espondence: [email p o ec ed]
Abs ac :
The ongoing Co ona i us disease 2019 (COVID-19) pandemic has changed he wo king
en i onmen , occupa ion, and li ing s yle o billions o people a ound he wo ld. The se e es impac
o he co ona i us is on mig an communi ies; hence, i is ele an o assess he economic impac
and men al s a us o he Indian mig an s. This s udy is quan i a i e in na u e and based on a sample
su ey o 180 mig an wo ke s. Desc ip i e s a is ics, chi-squa e es , dependen sample - es , and
Pea son’s co ela ion coe ﬁcien we e u ilized o analyze he su eyed da a. The ﬁndings o he s udy
e eal, h ough he wo king expe ience o he mig an s, ha new in e na ional mig a ion has educed
due o lockdown and in e na ional a el es ic ions. I was also epo ed ha he majo i y o he
mig an s wo ked less han he no mal wo king hou s du ing he lockdown, causing a educ ion
o sala y and emi ances. Chi-squa e es conﬁ ms ha he pe cep ions o mig an s owa ds he
COVID-19 managemen by he go e nmen we e signiﬁcan ly di e en in opinion by di e en
occupa ion/p o ession. Majo i y o he sampled mig an s epo ed he p oblem o ne ousness,
anxie y, and dep ession; howe e , hey we e also hope ul abou he u u e. The psychological
p oblem was se e e o he mig an s abo e he age o 40, no educa ed, and wi h a highe numbe
o amily membe s. Subsequen ly, he policy implica ions om he ﬁndings o he esea ch can
d aw a en ion o he policy make s owa ds p o ec i e measu es which need o be implemen ed o
suppo mig an s du ing he ongoing pandemic. The go e nmen should ake some necessa y s eps,
such as a ﬁnancial beneﬁ scheme, o o e come he p oblems in he educ ion o mig an ea nings
and emi ances. The go e nmen should no ocus only on accina ion and physical ﬁ ness o he
mig an s bu also need o ﬁnd ou he cu e o he psychological impac a ising du ing he pandemic.
Keywo ds:
COVID-19; pandemic; mig an s; sample su ey; employmen s a us; emi ances; mi-
g an s’ pe cep ion; economic and psychological impac s
1. In oduc ion
The dange ous ongoing pandemic, Co ona i us disease 2019 (COVID-19), epo ed
in Wuhan ci y, China, in Decembe 2019 and i is caused by a no el co ona i us called
SARS co ona i us 2 (SARS-CoV-2) [
1
]. The di ec o gene al o he Wo ld Heal h O gani-
za ion (WHO) ini ially decla ed he sp ead o co ona i us as a public heal h eme gency
o in e na ional conce n on 30 Janua y 2020. La e on, he WHO decla ed a pandemic on
11 Ma ch 2020 [2].
The no el co ona i us is unique in na u e because o high man- o-man
ansmission and has sp ead o 176 million people wo ldwide and caused 3.8 million
dea hs as o 15 June 2021 [
3
]. This pandemic has changed he occupa ion and li ing s yle
o billions o people a ound he wo ld and aised ques ions o medical acili y a ange-
men s o he di e en coun ies o he wo ld. The go e nmen o China s a ed imposing
es ic ions and he lockdown in Wuhan ci y began on 23 Janua y 2020, ollowed by India
Heal hca e 2021,9, 1152. h ps://doi.o g/10.3390/heal hca e9091152 h ps://www.mdpi.com/jou nal/heal hca e
47
Heal hca e 2021,9, 1152
on 24 Ma ch and Saudi A abia on 25 Ma ch 2020 [
4
]. The main objec i e o he lockdown
o cu ew is o limi he sp ead o he i us by main aining social dis ancing and c ea ing
medical acili y on wa oo ing. Lockdown; banned public ga he ings; suspending eligious
ac i i ies; closu e o business, schools, colleges, e c.; cu ews; and es ic ion o suspension
o all he a el domes ically as well as in e na ionally we e ollowed by he majo i y o
coun ies as p e en a i e measu es. The go e nmen o Saudi A abia had suspended all
i s in e na ional ﬂigh s on 15 Ma ch 2020 and esumes a e 14 mon hs on 17 May 2021;
howe e , he suspension o ﬂigh s will con inue o 13 coun ies, including India due o he
second wa e o co ona i us [5].
The COVID-19 pandemic is no only a heal h eme gency bu also a labo ma ke
and economic c isis because o i s e ec s on he business s a us o millions o indi id-
uals. The Saudi heal h minis y ook he ini ia i e o p o ide ee co ona accine and
also o e ed ee co ona sc eening and heal h ca e se ices o all o i s ci izen, including
mig an s wo ke s, and made accine compulso y o he heal h ca e wo ke s pa icipa ing
in Hajj and Um ah (Islamic pilg image o Mecca) ini ially and la e on made i compulso y
o all male and emale p i a e and public sec o wo ke s o a end he wo kplace [
5
–
7
].
COVID-19 immuniza ion will be equi ed o pa icipa e in any socio-cul u al, comme cial,
economic, en e ainmen , o suppo ing a ai s in Saudi A abia om
1 Augus 2021 [7,8]
.
The go e nmen o Saudi A abia is s ic owa ds he en o cemen o COVID-19 egula-
ions o educe i s sp ead and iola o s a e ﬁned be ween Saudi Riyal (SAR) 10,000 o
SAR 100,000; howe e , a second wa e o COVID-19 hi he coun y in he beginning o
Feb ua y 2021 [9].
Acco ding o Indian Census-2011, India had 45.6 c o e mig an popula ion (38%) and,
acco ding o he ecen epo published by “Uni ed Na ions Depa men o Economic and
Social A ai s—2019”, India con inues o ha e he maximum o i s people (17.5 million)
li ing o e seas and highes emi ance ecei ing coun y (USD 78.6 billion). Saudi A abia
is he hi d op emi ances sending coun y (USD 36.1 billion) in he wo ld and anked
hi d (13 million) in la ges numbe o in e na ional mig an s in he wo ld. India–Saudi
A abia shi ed om he en h (2000–2010) o se en h la ges bila e al mig a ion co ido in
he wo ld [10,11].
The COVID-19 pandemic had educed he new in e na ional mig a ion and inc eased
he e u nee mig an s, which happens o be he ﬁ s ime in ecen his o y. Acco ding o
an es ima e by Wo ld Bank, a o al o 6,000,000 mig an s we e e acua ed h ough special
ﬂigh s (Vande Bha a Mission) and Ke ala was a ec ed he mos by 4,000,000 e u nee
mig an s. The es ima ed emi ances (Wo ld Bank) o India will all by 9% in 2020 and
14% in 2021 and he ﬂow o o eign di ec in es men will all by 36% in 2020; howe e ,
India will con inue o be he op emi ance ecipien coun y globally, wi h app oxima ely
USD 76 billion which will be 2.9% o i s G oss Domes ic P oduc (GDP). The mone a y
eme gency accen ua ed by COVID-19 could be long, p o ound, and inescapable when
seen h ough a eloca ion ocal poin [
12
]. The oil ich coun y and job- ich sec o in Saudi
A abia was d as ically a ec ed by Co ona i us because o he d op in ade, dis up ion o
p oduc ion, ou ism (Hajj and um ah), and hospi ali y. Lockdown and a el es ic ion
educe he demand o oil globally, and consequen ly oil p ices had allen by 50% in
Ma ch 2020
. To ecupe a e he economic slowdown, he Saudi go e nmen allowed p i a e
sec o companies o cu he sala ies o he wo ke s up o 40% o a pe iod o six mon h and
he ea e could also e mina e he con ac [
13
,
14
]. The majo i y o he mig an wo ke s in
Saudi A abia a e engaged in he cons uc ion sec o , ag icul u e, hospi ali y, and domes ic
wo k, which a e highly a ec ed by he ongoing pandemic. The acu ely a ec ed mig an s
in he s a e du ing he pandemic a e domes ic wo ke s, low skilled/low-income wo ke s,
con ac e mina ed o comple ed wo ke s, in o mal wo ke s, women mig an wo ke s,
and sala ied employees. In his con ex , he p esen s udy a emp s o make a deepe
analysis o economic and psychological impac s o COVID-19 pandemic on Indian mig an
wo ke s in Saudi A abia. The pape is coo dina ed as ollows: Sec ion 1 is in oduc o y,
Sec ion 2 e iews he li e a u e, Sec ion 3 desc ibes he esea ch gap, Sec ion 4 delinea es
48
Heal hca e 2021,9, 1152
ȱ
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
Below1000 1000Ͳ3000 3000Ͳ5000 Abo e5000
Remi ances(inSAR)
AxisTi le
Remi ancesBe o eandDu ingLockdown
Be o eLD Du ingLD
Figu e 2. Change in emi ances du ing he pandemic.
5.5. Dependen Sample -Tes
Dependen o pai ed sample - es is used o compa e he di e ences in he alue
o same sample a wo di e en imes. To es whe he he compa ison o emi ances
shown in Figu e 2 is s a is ically signiﬁcan , a - es is applied. The null hypo hesis
was ‘ he e is no s a is ical di e ence in emi ances be o e and du ing he lockdown
o he pandemic’. The mean and s anda d de ia ion o emi ances be o e lockdown
we e es ima ed o be
1.78 and 0.917,
espec i ely, and du ing lockdown he mean = 1.62
and
S d. De ia ion = 0.885.
Table 4 desc ibe he esul s o he pai ed - es . T s a is ics o
3.924 wi h 179 deg ee
o eedom co esponded o he p- alue = 0.000, which is less han
0.05; he e o e, we ejec he null hypo hesis. I means ha he e is s a is ically a di e ence
in he emi ances be o e and du ing lockdown
Table 4. Pai ed Sample -Tes .
Pai ed Sample -Tes
95% Conﬁdence In e al o he Di e ence
Mean S d. De ia ion S d. E o Mean Lowe Uppe d p-Value
Remi ances be o e
lockdown—Remi ances du ing lockdown 0.161 0.551 0.041 0.080 0.242 3.924 179 0.000
Sou ce: Calcula ed by he au ho s om Google Fo m ques ionnai e.
5.6. Mig an s’ Pe cep ion o he COVID-19 Managemen by he Go e nmen o Saudi A abia
The esea che s used six ques ions o assess esponden s’ pe cep ions o he
COVID-19
managemen by he go e nmen o Saudi A abia. The esponses we e egis e ed in a ﬁ e-
poin Like scale a ying om ‘ e y good’ o ‘ e y poo ’, as p esen ed in Table 5. The
mig an s we e ound o be sa isﬁed wi h he COVID p o ec ion ela ed in o ma ion p o-
ided by he go e nmen . In o al, 51.1% esponded ‘ e y good’, 46.1% esponded as
‘good’, only 2.8% belie ed ha ‘a e age’ in o ma ion was p o ided, and none o he mi-
g an s esponded ‘poo ’ o ‘ e y poo ’. Hal o he mig an s epo ed ‘ e y good’ and
48.9% esponded ‘good’ in ega d o sa e y measu es aken by he Saudi go e nmen .
Almos he same pe cep ion was ound in he case o medical acili ies p o ided by he
go e nmen : 54.4% epo ed as e y good, 44.4% as good, and only 1.1% we e a e age.
In esponse o whe he mig an s had aced any di ﬁcul ies sending money o hei amily
du ing he lockdown pe iod, 51.1% epo ed ‘ e y good’, 42.8% epo ed ‘good’, 3.9%
epo ed ‘a e age’, and only 2.2% epo ed ‘poo ’ acili ies o send money du ing he lock-
55

Heal hca e 2021,9, 1152
down pe iod. The esea che s also asked abou he ood and o he basic acili ies p o ided
by he go e nmen : 46.7% esponded ‘ e y good’ and ‘good’ sepa a ely; howe e , 6.7%
esponded ‘a e age’. Fu he mo e, 46.1% o he esponden s epo ed ‘ e y good’ li ing
condi ions, 49.4% esponded ‘good’, and only 4.4% epo ed ‘a e age’ li ing condi ion
du ing he lockdown pe iod.
Table 5. Pe cep ions o he mig an s owa ds COVID-19 managemen by Go e nmen o Saudi A abia.
S a emen Ve y Good Good A e age Poo Ve y Poo To al
COVID p o ec ion ela ed in o ma ion by Saudi Go . 51.1% 46.1% 2.8% NIL NIL 100.0%
Sa e y measu es aken by Saudi Go e nmen 50.0% 48.9% 1.1% NIL NIL 100.0%
Medical acili y p o ided by Saudi Go e nmen 54.4% 44.4% 1.1% NIL NIL 100.0%
Facili y o send money o India du ing lockdown 51.1% 42.8% 3.9% 2.2% NIL 100.0%
Food and o he acili ies p o ided by Saudi Go e nmen 46.7% 46.7% 6.7% NIL NIL 100.0%
Li ing condi ions in Saudi A abia du ing lockdown 46.1% 49.4% 4.4% NIL NIL 100.0%
Sou ce: Calcula ed by he au ho s om Google Fo m ques ionnai e.
5.7. Mig an s’ Pe cep ions o COVID-19 Managemen by Go e nmen o India
The esea che s also ied o analyze he pe cep ions o he mig an s owa ds he
acili y p o ided in he e acua ion o mig an s du ing he lockdown pe iod. Two ques ions
we e asked o he esponden s, and esponses a e p esen ed in Table 6. The ﬁ s ques ion
was ela ed o he help p o ided by he embassy o India in Saudi A abia: 33.9% o he
esponden s epo ed ‘ e y good’, 56.1% esponded ‘good’, 7.2% esponded ‘poo ’, and
0.6% esponded ‘ e y poo ’. This ques ion was ele an because some mig an s may
ace he p oblem o isa expi y, passpo enewal, o issues ela ed o wo king con ac s.
The second ques ion was ela ed o he e acua ion o he mig an s h ough anspo
acili ies: 56.1% o he esponden epo ed ‘ e y good’, 31.7% epo ed ‘good’, 8.3%
epo ed ‘a e age’ and 3.9% esponded ‘ e y poo ’. This ques ion was also ele an
because he unce ain y which a ises due o he sp ead o Co ona i us o ces mig an s o
e u n o India.
Table 6. Mig an ’s pe cep ions owa ds COVID managemen by Go e nmen o India.
S a emen s Ve y Good Good A e age Poo Ve y Poo To al
Help p o ided by Embassy o India in Saudi A abia 33.9% 56.1% 7.2% 2.2% 0.6% 100.0%
T anspo acili y p o ided by Go e nmen o India 56.1% 31.7% 8.3% 3.9% NIL 100.0%
Sou ce: Calcula ed by he au ho s om Google Fo m ques ionnai e.
5.8. Combined Mean o Pe cep ions
Table 7 p esen s he combined mean o he pe cep ions owa ds COVID-19 manage-
men by he Go e nmen o India and Go e nmen o Saudi A abia. A lowe mean alue
indica es be e pe cep ions. The combined mean o he pe cep ions owa ds go e nmen
o Saudi A abia is 1.54, which is less han he combined mean alue 1.7 o he pe cep ion
owa ds he go e nmen o India. This esul shows ha he go e nmen o Saudi A abia
managed COVID-19 be e han he go e nmen o India acco ding o mig an s’ pe cep-
ions. Howe e , his pe cep ion is based on ew a iables and he esponses o he mig an s
a ailable in Saudi A abia du ing lockdown pe iod.
56
Heal hca e 2021,9, 1152
Table 7. Combined mean o he pe cep ions.
Pe cep ions N Minimum Maximum Mean S d. De ia ion
Pe cep ion owa ds
go e nmen o India 180 1 5 1.7 0.76
Pe cep ion owa ds
go e nmen o Saudi A abia
180 1 4 1.54 0.58
Sou ce: Calcula ed by he au ho s om Google Fo m ques ionnai e.
5.9. Chi-Squa e Tes
A chi-squa e es was applied o disco e he associa ion be ween pe cep ions o
COVID-19 managemen by he go e nmen ac oss he di e en p o essions/occupa ions.
The sample da a o occupa ional s uc u e we e classiﬁed as P o essionals, Technicians,
Cle ical Suppo Wo ke s, Se ice and Sales Wo ke s, Elemen a y Occupa ion, Plan and
Machine Ope a o , and o he s. The null hypo hesis was ‘The e is no signiﬁcan di e ence
in he opinion/pe cep ion o he mig an wo ke s owa ds he COVID-19 managemen by
he go e nmen ac oss di e en occupa ions’, and he al e na i e hypo hesis was ‘ he e
is signiﬁcan di e ence in he opinion/pe cep ion o he mig an wo ke s owa ds he
COVID-19
managemen by he go e nmen ac oss di e en occupa ions. The ela ionship
be ween hese a iables was ound o be signiﬁcan as calcula ed by chi-squa e alue
and
p- alue
which is less han 0.05 (5% le el o signiﬁcance) as p esen ed in he Table 8.
The e o e, we ejec he null hypo hesis. I means ha he e was a signiﬁcan di e ence
in opinion o he mig an wo ke s owa ds he COVID-19 managemen by he go e n-
men o Saudi A abia and India. P o essionals, echnicians, and elemen a y occupa ional
wo ke s we e ound o ha e low nega i e opinion owa ds COVID-19 managemen by he
go e nmen , especially owa ds anspo acili ies p o ided by he go e nmen o India,
help p o ided by he embassy o India, and acili ies o send money om Saudi A abia
o India. Howe e , cle ical suppo wo ke s, se ice and sales wo ke s, and plan and
machine ope a o s had highly posi i e opinions conce ning he COVID managemen by
he go e nmen .
Table 8.
Chi-Squa e Analysis o Pe cep ions o COVID-19 Managemen by Go . Wi hin Di e en P o essions/Occupa ions.
Pe cep ions Chi Squa e Value p-Value
COVID p o ec ion ela ed in o ma ion by Saudi Go e nmen 51.36 0.000
Sa e y measu es aken by Saudi Go e nmen 29.18 0.004
Medical acili y p o ided by Saudi go e nmen 21.64 0.042
Facili y o send money o India du ing lockdown 39.44 0.002
Help p o ided by Embassy o India in Saudi A abia 56.37 0.000
T anspo acili y p o ided by Go e nmen o India 40.14 0.002
Food & o he acili y p o ided by Saudi Go e nmen 28.86 0.004
Li ing condi ion in Saudi A abia du ing lockdown 36.02 0.000
Sou ce: Calcula ed by he au ho s om Google Fo ms ques ionnai e.
5.10. Compa ing he Pe cep ions o Mig an s wi h O he Ci izens
Pe cep ions o he ci izens o mig an s may di e o be he same in di e en coun ies,
depending upon he in as uc u e and decisions aken by he go e nmen . Se e al s udies
we e ca ied ou o in es iga e he pe cep ions o he ci izens o mig an s in a coun y. Fo
ins ance, a s udy on he pe cep ion o heal h ca e wo ke s du ing he COVID-19 pandemic
in he case o Saudi A abia was conduc ed, which conﬁ med ha he majo i y o he
esponden s (93.6%) we e happy and el sa e in ega d o he go e nmen decision o
lockdown and 94.7% suppo ed he a el es ic ion imposed by he go e nmen [
33
].
Simila ly, ou s udy also conﬁ ms ha he majo i y o he mig an s s ongly ag eed o
ag eed wi h he go e nmen decision. Fo ins ance, 97.2% o he mig an s ag eed wi h he
in o ma ion p o ided by Saudi go e nmen ela ed o he p o ec ion om Co ona i us. In
o al, 98.8% o he esponden s we e happy wi h he sa e y measu es aken by he Saudi
57
Heal hca e 2021,9, 1152
go e nmen . Ano he s udy was conduc ed o explo e he pe cep ion o he public o
he go e nmen o Singapo e in ela ion o COVID-19 ela ed in o ma ion. The esul s o
he s udy conﬁ m ha majo i y o he esponden s (99.1%) ag eed o s ongly ag eed on
he COVID-19 ela ed in o ma ion p o ided by he go e nmen and 97.9% belie ed he
Singapo e news agency [
34
]. Ano he s udy was ca ied ou in Bangladesh o explo e he
public pe cep ion o go e nmen measu es ela ed o COVID-19. The esul o he sample
su ey e eals he ac ha he majo i y o he esponden s (58%) we e no sa isﬁed by he
measu es aken by he go e nmen o Bangladesh. Howe e , 40% o he esponden s we e
ound o be sa isﬁed wi h go e nmen decisions [
35
]. Ou s udy e eals he ac ha he
majo i y o he mig an s we e sa isﬁed by he decision aken by he Saudi go e nmen .
Ano he s udy o Bangladesh was conduc ed and e ealed he ac ha he majo i y o he
esponden s (62%) s ongly ag ee ha he heal hca e sys em was no able o handle he
pandemic and 68.6% belie e ha he go e nmen o Bangladesh needs suppo om he
public o handle he pandemic [
36
]. In ou s udy, 98.8% o he esponden s we e happy wi h
he medical acili ies p o ided by he go e nmen o Saudi A abia, 93.8% we e sa isﬁed
wi h he acili y o send money, 90% we e happy wi h he help p o ided by he embassy o
India, and 87.7% we e sa is y wi h he anspo acili y p o ided by go e nmen o India
du ing he lockdown pe iod.
5.11. Men al Heal h S a us o he Mig an s
COVID-19 had no only inﬂuenced he economic and physical heal h o he people bu
also hei men al s a us. This pandemic had d as ically changed he men al s a us o he
Indian mig an wo ke s in Saudi A abia. Table 9 desc ibes he le els o anxie y, dep ession,
and s ess among he mig an wo ke s. The majo i y o he mig an s eel ne ous (67.8%),
dep essed (63.3%), and lonely (72.2%) du ing he pandemic. I was also epo ed ha
70% had di ﬁcul ies in concen a ing and 66.7% had a ha d ime in sleeping; howe e , he
majo i y o hem (91.7%) we e eeling hope ul abou he u u e, which shows sil e lining
a he end o he unnel. I was also obse ed ha only 2.2% o he mig an s we e Co ona
posi i e, 1.7% o hei membe households we e Co ona posi i e, and mos o hem (78.3%)
we e no sca ed o i us.
Table 9. Men al heal h o he mig an s du ing pandemic.
S a emen s Va iables F equency (%)
Ha e you el ne ous, anxious, o on edge? Yes 122 67.80%
No 58 32.20%
Ha e you el dep essed? Yes 114 63.30%
No 66 36.70%
Ha e you el lonely? Yes 130 72.20%
No 50 27.80%
Ha e you el hope ul abou he u u e? Yes 165 91.70%
No 15 8.30%
I ha e a ha d ime sleeping because o he Co ona Yes 120 66.70%
No 60 33.30%
I ha e had di ﬁcul ies concen a ing because o Co ona Yes 126 70.00%
No 54 30.00%
Ha e you been es ed Co ona posi i e in Saudi A abia? Yes 4 2.20%
No 176 97.80%
A e you sca ed o Co ona i us? Yes 39 21.70%
No 141 78.30%
Does any o you amily membe in ec ed o Co ona i us? Yes 3 1.70%
No 177 98.30%
Sou ce: Calcula ed by he au ho s om Google Fo ms ques ionnai e.
58
Heal hca e 2021,9, 1152
5.12. Compa ison o Men al Heal h o he Mig an s by Age, Domicile and Educa ion
5.12.1. Fel Ne ous, Anxious, o on Edge
Figu e 3 desc ibes eeling ne ous, anxious, o on edge du ing pandemic by Indian
mig an s in Saudi A abia. A ound hal o he young popula ion aged be ween 20 o 40 el
ne ous, and 78.5% o he mig an s be ween he age o 40 o 50 and 90% o he age g oup
abo e 50 el ne ous du ing he pandemic. The sample da a e eal he ac ha young
mig an s we e less ne ous han olde mig an s. The mig an s om Biha we e ound
o be less ne ous han U a P adesh and o he s a es o India. The ne ousness o he
mig an s was also inﬂuenced by he le els o educa ion o he mig an s. Highe le el o
educa ion implies a lowe le el o ne ousness: 25% o doc o a e, 59% o pos -g adua es,
64% o g adua es epo ed ne ousness du ing pandemic; howe e , 75% o in e media e,
79% o high school educa ed, and 61.5% o uneduca ed mig an s epo ed ne ousness.
To in es iga e he ela ionship be ween ne ous eeling by age, domicile, and educa ion,
co ela ion coe ﬁcien was applied. The esul o co ela ion coe ﬁcien is shown in Table 10.
Pea son’s co ela ion be ween el ne ous and age o he mig an s was ound o be nega i e
and s a is ically signiﬁcan ( =
−
0.311, p< 0.01). Simila ly, he ela ionship be ween el
ne ous and domicile o he mig an s was ound o be posi i e and s a is ically signiﬁcan
( = 0.262, p< 0.01). Howe e , he ela ionship be ween el ne ous and educa ion le el o
mig an s was ound o be posi i e bu s a is ically insigniﬁcan ( = 0.133, p> 0.01).
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20–30
30–40
40–50
50–60
UP
Biha
O he
No Educa ed
HighSchool
In e media e
G adua ion
Pos ͲG adua ion
Doc o a e
Age Domicile Educa ion
Ha e you el ne ous, anxious, o on edge? Yes No
Figu e 3. Compa ison o eeling ne ous.
5.12.2. Fel Dep essed
Figu e 4 ep esen s he le el o dep ession among he sample mig an wo ke s du ing
he pandemic. Less han hal o he young mig an s aged be ween 20 o 40 epo ed eeling
dep essed, howe e 72% o he mig an s be ween he ages o 40 o 50 and 90% o he
mig an s aged abo e 50 epo ed eeling dep essed du ing he pandemic. The sample
da a e eal ha young aged mig an s we e less dep essed han old age mig an s. The
84.1% mig an s om U a P adesh epo ed eeling dep ession, howe e only 18.8% o he
mig an s om Biha epo ed dep ession and 64.5% om o he s a es we e in dep ession
du ing he pandemic. Lowe le els o dep ession we e epo ed by highly educa ed
mig an s (25% o doc o a e, 54% o pos g adua e, and 56% o g adua e) and uneduca ed
mig an s (53%); howe e , 75% o he in e media e and high school educa ed mig an s
epo ed dep ession. To in es iga e he ela ionship be ween eelings o dep ession by
age, domicile, and educa ion, a co ela ion coe ﬁcien was applied. The esul o he
co ela ion coe ﬁcien is shown in Table 11. Pea son’s co ela ion be ween el dep essed
59
Heal hca e 2021,9, 1152
and age o he mig an s was ound o be nega i e and s a is ically signiﬁcan ( =
−
0.368,
p< 0.01
). Simila ly, he ela ionship be ween el dep essed and he domicile o he mig an s
was ound o be posi i e and s a is ically signiﬁcan ( = 0.236, p< 0.01). Howe e , he
ela ionship be ween el dep essed and educa ion le el o mig an s was ound o be
posi i e bu s a is ically insigniﬁcan ( = 0.140, p> 0.01).
Table 10. Pea son’s co ela ion ma ix.
S a emen s Age p-Value
Pea son Co ela ion
Fel Ne ous, Anxious, o on Edge −0.311 0.000
Fel Dep essed −0.368 0.000
Fel Lonely −0.333 0.000
Ha d ime sleeping −0.372 0.000
Di ﬁcul ies in concen a ion −0.315 0.000
Hope ul abou he u u e −0.132 0.077
S a emen s Domicile p-Value
Pea son co ela ion
Fel Ne ous, Anxious, o on Edge 0.262 0.000
Fel Dep essed 0.236 0.001
Fel Lonely 0.178 0.017
Ha d ime sleeping 0.320 0.000
Di ﬁcul ies in concen a ion 0.289 0.000
Hope ul abou he u u e 0.165 0.027
S a emen s Educa ion p-Value
Pea son co ela ion
Fel Ne ous, Anxious, o on Edge 0.133 0.075
Fel Dep essed 0.140 0.061
Fel Lonely 0.106 0.158
Ha d ime sleeping 0.175 0.019
Di ﬁcul ies in concen a ion 0.151 0.044
Hope ul abou he u u e 0.027 0.717
S a emen s Numbe o Family Membe p-Value
Pea son co ela ion
Fel Ne ous, Anxious, o on Edge −0.403 0.000
Fel Dep essed −0.464 0.000
Fel Lonely −0.382 0.000
Ha d ime sleeping −0.446 0.000
Di ﬁcul ies in concen a ion −0.429 0.000
Hope ul abou he u u e −0.143 0.055
60

Heal hca e 2021,9, 1152
ȱ
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20–30
30–40
40–50
50–60
UP
Biha
O he
No Educa ed
HighSchool
In e media e
G adua ion
Pos ͲG adua ion
Doc o a e
Age Domicile Educa ion
Ha eyou el dep essed? Yes No
Figu e 4. Compa ison o eeling dep essed.
Table 11. Compa ison o psychological e ec by numbe o amily membe s.
S a emen s Le els Numbe o Family Membe
Below 5 5 o Mo e
Ha e you el ne ous, anxious, o on edge? Yes 50.0% 77.5%
No 50.0% 22.5%
Ha e you el dep essed? Yes 35.9% 78.4%
No 64.1% 21.6%
Ha e you el lonely? Yes 53.1% 82.8%
No 46.9% 17.2%
Ha e you el hope ul abou he u u e? Yes 87.5% 94.0%
No 12.5% 6.0%
I ha e a ha d ime sleeping because o he o ona Yes 42.1% 80.2%
No 57.9% 19.2%
I ha e had di ﬁcul ies concen a ing because o co ona Yes 50.0% 81.1%
No 50.0% 18.9%
5.12.3. Fel Lonely
Figu e 5 shows he loneliness among he di e en ypes o he mig an s. The mig an s
in he age g oup o below 40 epo ed less loneliness han he mig an s abo e he age o 40.
All mig an s abo e he age o 50 epo ed ha hey el lonely du ing he pandemic; how-
e e , 78.5% in he age g oup o 40 o 50, and a ound 56% o he age below 40 epo ed eeling
loneliness du ing he pandemic. The mig an s om Biha we e eeling less loneliness han
he mig an s om o he s a es o India. The loneliness among di e en ly educa ed mig an s
we e no educa ed mig an s (61.5%), high school (86.2%), in e media e (77.1%), g adua ion
(67.2%), pos -g adua ion (72.7%), and doc o a e only 25%. To in es iga e he ela ionship
be ween el lonely by age, domicile and educa ion, a co ela ion coe ﬁcien was applied.
The esul o he co ela ion coe ﬁcien is shown in Table 10. Pea son’s co ela ion be ween
el lonely and age o he mig an s was ound o be nega i e and s a is ically signiﬁcan
( =
−
0.333, p< 0.01). Simila ly, he ela ionship be ween el lonely and domicile o he
mig an s was ound o be posi i e and s a is ically signiﬁcan a he le el o 0.05 ( = 0.178,
61
Heal hca e 2021,9, 1152
p< 0.05). Howe e , he ela ionship be ween el lonely and educa ion le el o mig an s
was ound o be posi i e bu s a is ically insigniﬁcan ( = 0.106, p> 0.01).
ȱ
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20–30
30–40
40–50
50–60
UP
Biha
O he
No Educa ed
HighSchool
In e media e
G adua ion
Pos ͲG adua ion
Doc o a e
Age Domicile Educa ion
Ha eyou el lonely? Yes No
Figu e 5. Compa ison o eeling lonely.
5.12.4. Fel Hope ul abou he Fu u e
Figu e 6 exp esses he hope ulness abou he u u e by mig an wo ke s du ing he
pandemic. The majo i y o all age g oups o mig an s, om all s a es and le els o educa ion,
epo ed hoping o be e e en s o happen in he u u e; howe e , hope ulness in highly
qualiﬁed mig an s was epo ed o be less han in all o he mig an s. To in es iga e he
ela ionship be ween el hope ul abou he u u e and age, domicile, and educa ion, a
co ela ion coe ﬁcien was applied. The esul o co ela ion coe ﬁcien is shown in
Table 10.
Pea son’s co ela ion be ween el hope ul abou he u u e and age o he mig an s was
ound o be nega i e bu s a is ically insigniﬁcan ( =
−
0.132, p> 0.05). Simila ly, he
ela ionship be ween el hope ul abou he u u e and domicile o he mig an s was ound
o be posi i e and s a is ically signiﬁcan a he le el o 0.05 ( = 0.165, p< 0.05). Howe e ,
he ela ionship be ween el hope ul abou he u u e and educa ion le el o mig an s was
ound o be posi i e bu s a is ically insigniﬁcan ( = 0.027, p> 0.05).
5.12.5. Di ﬁcul ies in Sleeping and Concen a ion
Figu es 7 and 8 desc ibe he anxie y among mig an wo ke s h ough sleeping p ob-
lems and di ﬁcul y in concen a ing. The p oblem o anxie y was epo ed as mo e se e e
in he age g oup o abo e 40 han he age g oup below 40. I was also seen ha mig an s
who belongs o Biha we e ound o ha e less o an anxie y p oblem han he mig an s
om o he s a es. The p oblems o anxie y we e also co ela ed o he le el o educa ion
o he mig an s. Mo e educa ed mig an s epo ed less anxie y han he lowe educa ed
mig an s du ing he pandemic. To in es iga e he ela ionship be ween di ﬁcul y sleeping
and di ﬁcul ies in concen a ion by age, domicile, and educa ion, a co ela ion coe ﬁcien
was applied. The esul o he co ela ion coe ﬁcien is shown in Table 10. Pea son’s
co ela ion be ween di ﬁcul y sleeping and age o he mig an s was ound o be nega i e
and s a is ically signiﬁcan ( =
−
0.372, p< 0.01) and di ﬁcul ies in concen a ion and age
was also ound o be nega i e and s a is ically signiﬁcan ( =
−
0.315, p< 0.01). Simila ly,
he ela ionship be ween di ﬁcul y sleeping and domicile o he mig an s was ound o
be posi i e and s a is ically signiﬁcan ( = 0.320, p< 0.01) and he ela ionship be ween
di ﬁcul ies in concen a ion and domicile was also ound o be posi i e and s a is ically
signiﬁcan ( = 0.289, p< 0.01). The ela ionship be ween di ﬁcul y sleeping and educa ion
62
Heal hca e 2021,9, 1152
le el o mig an s was ound o be posi i e bu s a is ically signiﬁcan a he le el o 0.05. (
= 0.175, p< 0.05) and he ela ionship be ween di ﬁcul ies in concen a ion and educa ion
le el o he mig an s was also ound o be posi i e and s a is ically signiﬁcan a he le el
o 0.05 ( = 0.151, p< 0.05).
ȱ
0%
20%
40%
60%
80%
100%
20–30
30–40
40–50
50–60
UP
Biha
O he
No Educa ed
HighSchool
In e media e
G adua ion
Pos ͲG adua ion
Doc o a e
Age Domicile Educa ion
Ha e you el hope ul abou he u u e? Yes No
Figu e 6. Compa ison o eeling hope ul abou u u e.
ȱ
0%
20%
40%
60%
80%
100%
20–30
30–40
40–50
50–60
UP
Biha
O he
No Educa ed
HighSchool
In e media e
G adua ion
Pos Ͳ
G adua ion
Doc o a e
Age Domicile Educa ion
I ha e a ha d ime sleeping Yes No
Figu e 7. Compa ison o ha d ime sleeping.
5.12.6. Compa ison o Men al Heal h E ec by Numbe o Family Membe s
Table 11 p esen s he compa ison o men al heal h impac ed by numbe o amily
membe s o he mig an s. Sample da a disclose he ac ha numbe o amily membe s
is di ec ly ela ed o he psychological s ess on mig an s. Only 50% o mig an s wi h
amily membe s below 5 el ne ous, 35.9% dep essed, 53.1% lonely, 42.1% had a ha d
ime sleeping, and 50% had di ﬁcul ies in concen a ing; howe e , 77.5% o mig an s wi h
amily membe s equal o 5 o abo e el ne ous, 78.4% dep essed, 82.8% lonely, 80.2%
ha e a ha d ime sleeping, and 81.1% had di ﬁcul ies in concen a ion. The majo i y o he
mig an s (87.5% wi h amily membe below 5 and 94% wi h amily membe equal o 5 o
abo e) el hope ul abou he u u e. The psychological p oblems a e se e e in he case o
he mig an s abo e he age o 40 and mig an s wi h highe numbe o amily membe s,
63
Heal hca e 2021,9, 1152
because o social esponsibili y and low capabili ies o ace in e pe sonal challenges. To
es he hypo hesis and in es iga e he ela ionship be ween hese s a emen s and he
numbe o amily membe s, a co ela ion coe ﬁcien was applied. The esul o co ela ion
coe ﬁcien is shown in Table 9. Pea son’s co ela ion be ween hese s a emen s and he
numbe o amily membe s o he mig an s was ound o be nega i e and s a is ically
signiﬁcan . Howe e , he ela ionship be ween el hope ul abou he u u e and numbe o
amily membe is posi i e bu s a is ically insigniﬁcan ( = −0.143, p> 0.05).
ȱ
0%
20%
40%
60%
80%
100%
20–30
30–40
40–50
50–60
UP
Biha
O he
No Educa ed
HighSchool
In e media e
G adua ion
Pos Ͳ
G adua ion
Doc o a e
Age Domicile Educa ion
I ha e had di icul ies concen a ing Yes No
Figu e 8. Compa ison o ha ing di ﬁcul ies in concen a ion.
5.12.7. Compa ing he Psychological Impac on Mig an s be o e and du ing COVID-19
The esul s o he s udy conﬁ m ha 67.8% o he esponden mig an s epo ed
eeling ne ous and 63.3% we e dep essed due o he COVID-19 pandemic. The le el o
psychological impac is much highe and se e e among he mig an wo ke s han be o e.
One s udy was ca ied ou o ﬁnd ou he p e alence o dep ession among mig an wo ke s
in AL-Qassim, Saudi A abia, by aking a c oss-sec ional su ey o 400 wo ke s in 2016.
The esul s o he s udy conﬁ med ha 20% o he mig an s epo ed he symp om o
dep ession. I was also epo ed ha le el o dep ession a ied by age bu no by du a ion
o s ay [
37
]. Ano he simila s udy was conduc ed in 2011 o ﬁnd ou he p e alence o
dep ession among mig an wo ke s o UAE. The su ey esul s o he 239 samples e ealed
ha 25.1% o he mig an s epo ed symp oms o dep ession. They also concluded ha
p e alence o dep ession is co ela ed wi h physical illness. In he same s udy, 6.3% o
he esponden s epo ed suicidal idea ion and 2.5% had al eady a emp ed suicide [
38
].
Ano he s udy o ﬁnd ou he p e alence o dep ession among mig an wo ke s was ca ied
ou in case o Qa a in 2016, which epo ed ha 57.9% o he mig an s had symp oms
o dep ession [
39
]. Hence, i is clea ha he pe cen age o mig an s in ou s udy which
epo ed symp oms o dep ession and eeling ne ous is much highe han he ea lie
s udies; he e o e, he COVID-19 pandemic had a se e e psychological impac on Indian
mig an s wo king in Saudi A abia.
6. Limi a ions
The main limi a ions o he s udy a e ha i ocuses on he Indian male mig an s in
Saudi A abia wi h a sample da a o 180, howe e he sample o emale mig an s a e e y
less. I also uses ew es s and s a egies. The cu en s udy does no emphasis he e ec on
mig an ’s amily in India du ing pandemic. Apa om i , his s udy does no conside
COVID-19 accina ion p ocess, p oblems and i s impac on mig an s in Saudi A abia.
The u u e scope o s udy in his a ea needed o analyze he economic and psychological
64
Heal hca e 2021,9, 1151
ue in bo h ways, o hose who ge easily dis ac ed o hose who may ﬁnd di ﬁcul o
disconnec comp omising hei heal h and wellbeing [22].
On a di e en no e, [
18
] e e ha elewo king may also impai ca ee p og ession
because, when wo king emo ely, wo ke s a e less on he ada o possible p omo ions.
Wha is mo e, wo ke s may eel less connec ed o he o ganiza ion and miss he social
con ac and usual exchange wi h co-wo ke s ha can lead o ui ul collabo a ions [
30
]. In
his ega d, e . [
31
] a gues ha pe sonal in e ac ions ha e a supe io impac , pa icula ly
due o he enabled isual con ac . Video calls and simila in e ac i e de ices ail o mimic
his expe ience; hence, i is a guable ha new echnologies os e a pa icula ype o
dis ance among wo ke s.
2.2. Telewo king du ing he Pandemic
The e ec i e implemen a ion o elewo king as a means o mi iga e he seemingly
una oidable economic impac o he COVID-19 was especially ele an o coun ies such as
Po ugal, in which posi i e signs o economic g ow h we e appea ing p io o he pandemic
ou b eak. Th ough co e ing a leas he unc ions compa ible wi h wo king a a dis ance,
he beneﬁ s a e e iden since i allows wo ke s o keep hei jobs and allows ﬁ ms o
con inue de eloping hei ac i i y, educing he economic bu den [31].
Howe e , his measu e was implemen ed wi hou speciﬁc egula ions, only based on
a gene al ag eemen on elewo king o 2002, d awn on a di e en s age o ICT de elopmen
and EU-based policies and di ec i es egula ing wo k, in gene al, and assuming by de aul
ha he same p o isions would apply. Among hese, a e: EU Di ec i e 2003/88/CE,
abou wo king ime schedules; EU Di ec i e 89/391/CEE on wo k heal h and hygiene; EU
di ec i e 2019/1158 abou dealing wi h p o essional and amilia li e and; EU Di ec i e
2019/1152 on anspa en and p edic able wo k condi ions [
32
]. The highligh goes o
gene al igh s, such as he olun a y na u e o he wo k; espec o p i acy; da a p o ec ion;
heal h and sa e y measu es.
Only in June 2020, an au onomous amewo k, aimed a in o ming a possible Eu opean-
based di ec i e on digi aliza ion, was pu o h co e ing ou speciﬁc a eas: digi al com-
pe ence and job secu i y; connec ion and disconnec ion modali ies; a iﬁcial in elligence
and human con ol; espec o human digni y and igilance. The emphasis on hese a eas
p o ides cues abou he main conce ns o conduc ing wo k ac i i ies wi h such dependence
on ICT. Fu he mo e, a ew ecommenda ions a e d awn so as o p o ec he wo ke s’
igh s on hese condi ions, s a ing wi h being in o med abou all he ma e s ega ding
equipmen , wo king hou s (no mal and ex ao dina y), esponsibili ies, and cos s. O he
impo an p o isions ega d he cos s being comple ely co e ed by he employe ; he
ex ao dina y hou s eimbu se; he igh o sick lea es and, e y impo an ly, an e ﬁcien
and ai measu emen and moni o ing o wo king hou s so as o p o ec wo ke s om he
isk o p esen eeism.
Besides no knowing he impac s and e ec s on a wide a ay o indica o s in he
long- un, ei he ela ed o p oduc i i y and ﬁnancial aspec s, he indi idual and social
coping o he hypo he ical dissemina ion o elewo king is also unce ain.
The li e a u e pu s o h wo coping s a egies: “in eg a ion” and “segmen a ion”/
“sepa a ion” [
33
]; bo h a e based on how indi iduals ed aw cul u al bounda ies a ound
“wo k” and “home” when hese o e lap, as occu s in a elewo king o ma . These coping
s a egies, al hough gene alis , p o ide a concep ual lens o he p ac icali ies o accommo-
da ing he co-p esence o hese wo se ings wi h he e hical and alues wi h which hey
a e imbued [34].
In his ega d, a sepa a is app oach ea u es he co-p esence o “wo k” and “home”
by adhe ing o s ic empo al egimes as exp essed in ﬁxed o ﬁce hou s and closed-doo
spaces. Thus, symbolically as well as p ac ically, “wo k” and “home” a e kep apa . An
in eg a i e app oach, on he o he hand, ends o be mo e ﬂexible and is likely o ollow a
mo e laissez- ai e empo al egime, in eg a ing domes ic, pe sonal ac i i ies (as physical
exe cise) and p o essional ac i i ies in common spaces [35].
71

Heal hca e 2021,9, 1151
Unde pinning he coping s a egies lies a undamen al elemen ega ding he gen-
de ed di ision o household and childca e esponsibili ies [
36
]. Domes ic inequali ies a e
s ill a eali y, pa icula ly in coun ies wi h lowe le els o gende equali y and emale
empowe men [
37
,
38
] and, du ing he pandemic, hey appea o ha e inc eased, especially
amongs people wi h child en [
39
]. Mo e speciﬁcally, mo he s epo ed a dec ease in
wo king hou s and an inc ease in domes ic and house ca e ac i i ies, as well as supe is-
ing child en’s homewo k and didac ic ac i i ies [
39
,
40
], wi h a nega i e impac on hei
wellbeing [
36
]. This is in line wi h he gende ed expec a ions ha emained he same and,
despi e he expansion o women’s oles in he las decade wo king ou side he home, hey
a e s ill expec ed o pe o m mos o he domes ic and ca e wo k [41].
Wha is mo e, gende ed oles a e p esc ip i e and p osc ip i e o a i udes and be-
ha iou , and bo h ha e been e idenced, especially in he beginning o he pandemic, wi h
women epo ing mo e psychological dis ess and anxie y, and men epo ing s eng h,
mo e calm, and de e mina ion [42].
This o ced expe ience on elewo king is pe cei ed as an oppo uni y o ca alyse
“a wide adop ion o elewo king p ac ices also a e he c isis” [
42
]. Acco ding o he
Eu opean Founda ion o he Imp o emen o Li ing and Wo king Condi ions [
43
], mo e
han h ee qua e s o EU wo ke s p e e o wo k om home, a leas occasionally, e en
wi hou COVID es ic ions. Speciﬁcally, mos EU wo ke s indica e ha hey had a posi i e
expe ience o elewo king and, albei no exclusi ely, he mos a ou ed op ion is o
combine elewo king and on-si e wo k.
Howe e , he o e lapping o leisu e and wo king ime, domes ic and labou ou ines,
as well as he ICT in ensi e use a e known o impac heal h and wellbeing. The nega i e
e ec s a e mos ly psychological p essu e, s ess, ision p oblems, anxie y, headaches,
a igue, sleep diso de s, and skele al muscle unc ions [43].
In o de o coun e ac he physical and men al heal h impac o elewo k, and o
p omo e o e all heal hy beha iou s du ing he pandemic, public heal h communica ion
should no only ocus on messaging in o ma ion s ic ly ega ding COVID-19 in ec ion and
i s mi iga ion (e.g., p e alence, p og ession, dea h a e, mi iga ion measu es) bu also heal h
p omo ing beha iou s ela ed o he managemen o in-doo ime and physical exe cise.
Indeed, some ha e ad ised o he main enance o physical exe cise du ing lockdown
(e.g., [
44
]), and i has been a gued o help educing he nega i e heal h consequences o
COVID-19 qua an ine [45].
2.3. Occupa ional Heal h in Telewo k: The Impo ance o Physical Ac i i y
Acco ding o he Wo ld Heal h O ganisa ion [
46
], a heal hy wo k o ce is c ucial
o social and economic de elopmen . The WHO’s epo on occupa ional heal h s a es
ha he e is a con inuous wo-way in e ac ion be ween indi iduals and he physical and
psychological wo king en i onmen , as he la e may a ec , posi i ely o nega i ely, he
wo ke ’s heal h, and p oduc i i y is, in u n, dis u bed by he pe son’s well-being. In iew
o his, in o de o ensu e occupa ional heal h in elewo k in he con ex o COVID-19, i is
impo an o unde line he heal h isks and beneﬁ s associa ed wi h he sudden and la ge-
scale shi o elewo k, as well as he speciﬁc condi ions ha lead o be e psychological
and wo k ou comes [47].
Wi hin he Po uguese con ex , a quali a i e shi occu ed in Heal h p omo ion
ini ia i es, as e idenced in he o ﬁcial communica ion issued by The Na ional P og am o
Physical Ac i i y o he Gene al Heal h Depa men (2020a) [
42
]. Aimed a coun e ac ing
he demanding es ic ions, bo h esul ing om spending mo e ime a home collapsing
ou ines and spaces as om being limi ed o enjoy public spaces, heal h au ho i ies ha e
been o ce ul in ensuing speciﬁc ecommenda ions adap ed o he ci cums ances. Ve y
di ec i e sugges ions included: a oiding o sea o lie down o mo e han 30 min; educe
he ime spen using echnological de ices; walk inside he house and conduc o he
physical ac i i ies; ‘in es in ac i i ies o cogni i e s imula ion ( eading, puzzles); s e ch
and medi a e as well as play wi h child en [48,49].
72
Heal hca e 2021,9, 1151
This is backed up by WHO, sugges ing 30 min o in ense o mode a ed physical
ac i i y ([
49
]), pa icula ly ega ding olde ci izens [
50
,
51
], gi en hei highe ulne abili y
o heal h p oblems and COVID-19. In his ega d, ae obic home exe cise has been ad ised,
due o i s ai ly low complexi y, low isk o inju y, and high popula i y [52].
Also, physical ac i i y seems o be nega i ely co ela ed o ca dio ascula disease
and diabe es (e.g., [
53
]), which is especially no ewo hy in he con ex o COVID-19, gi en
ha hese cons i u e isk ac o s associa ed o espec i e se e i y and mo ali y (e.g., [
53
]).
Addi ionally, exe cise has been epo ed o posi i ely impac an i-inﬂamma o y esponse
and educe immunologic abno mali y [54,55].
I is sel -e iden ha physical ac i i y has been impac ed by he global e o s o
mi iga e he p og ession o COVID-19 in ec ions [
56
]. In his social dis ancing phase,
he ype o physical ac i i y should p io i ize in e io s o secu e emp y public spaces.
Addi ionally, e . [
45
] pu s o h ha people should p ac ice physical exe cise ﬁ e o se en
imes a week, depending on he aining in ensi y and modali y ( o example, i is esis ance
aining i should be done wo o h ee imes a week, acco ding o [57].
Howe e , se e al obs acles may hinde he engagemen o a -home physical exe cise,
namely he una ailabili y o aining ma e ials and equipmen o mode a e o in ensi e
physical ac i i y (pa icula ly om hose wi h a lowe socio-economic le el wi h less
ma gin o acqui e hem), as well as di ﬁcul ies in con olling aining a iables, such as
adequacy o aining exe cises.
No wi hs anding he obs acles, one may a gue ha he dis up ion o no mal li e
and ou ines, allied o he sudden o ﬁcial Public Heal h communica ion issued by go -
e nmen s and ein o ced by all media, led o a salience o physical ac i i y in peoples’
minds. E en hough physical ac i i y p omo ion and heal hie li es a e wo common
claims in wes e n socie ies, he pandemic added a one o h ea and u gency o i , ei he as
a way o ein o ce he o e all physical heal h o o mi iga e he psychological impac o he
qua an ine measu es.
In his ega d, mo e ﬁne- uned esea ch is needed o conclude he impac o he
pe cep ion o public heal h messaging on he popula ion
´
s adhe ence o go e nmen al
guidelines, including he appeal o physical exe cise, as people end o comply wi h
go e nmen al sugges ions/o ien a ions e en when dis us ing he go e nmen . This is
pa icula ly ue in a ime whe e in o ma ion is no exclusi ely deli e ed di ec ly by he
ins i u ions bu a he media ed by bo h adi ional and social media [
58
] wi h po en ial
impac no only on compliance bu also on men al heal h (e.g., [
59
,
60
]). In he con ex o
COVID-19, s udies sugges ha using deon ological mo al ad ice when communica ing
public heal h ad ice (e.g., elici ing a sense o ci ic du y, e hical sel -ca e) con ibu es o he
engagemen o beha iou s ha a e help ul o heal h and wellbeing [61].
The ing ained no ion o how impo an physical exe cise is o physical and men al
heal h ound a mo e e ile g ound because o he lack o pa allel dis ac ions.
Digi al landscapes (wi h emphasis o YouTube and social media) played a quin essen-
ial ole in his dissemina ion, uelling a wide a ie y o online aining o e s, hus, ex-
panding he ou each o gymnasium, spo clubs, and pe sonal aine s. Reco ded and
li e sessions, mimicking physical aining, push good p ac ices and physical ac i i y sup-
po u he , o en on a daily basis [
62
], wi h he common denomina o o being mainly
home-based.
One may u he a gue ha physical ac i i y also con ibu es o mi iga e he p esen-
eeism and cogni i e o e load o connec ion, known o unde pin physical and emo ional
exhaus ion. In his ega d, i is ano he aspec o ake in o accoun when d a ing guidelines
a EU le el.
D awing on da a collec ed du ing he ﬁ s locked down, he p esen wo k con ibu es
o un eil key elemen s ha may be conside ed in communica ion and public policies
ega ding elewo king and physical ac i i y ailo ed o each di e en segmen ed g oups
o he popula ions.
73
Heal hca e 2021,9, 1151
3. Ma e ials and Me hods
3.1. Pa icipan s and P ocedu e
Da a was collec ed om 14 Ma ch 2020 o 2 o May h ough an online su ey in google
o ms which was sha ed ia ins i u ional and pe sonal con ac s. The e we e 1148 pa ici-
pan s who eplied, 69.9% women (n= 802) and 30.1% men (n= 346). The sample includes
ﬁ e di e en age g oups: un il 18 yea s old (n= 8; 0.7%); 18–24 yea s old (n= 277; 24.1%);
25–39 yea s old (n= 261; 22.7%); 40–59 yea s old (n= 466; 40.6%); abo e 60 yea s old
(
n= 136
; 11.2%). A subs an ial pe cen age o ou sample has high educa ion s udies: nea ly
hal is g adua ed a BSc le el (n= 563; 49%), 19.8% a Mas e le el (n= 227), and 7.1% has
a PhD (n= 81). 15.9% (n= 182) has ﬁnished middle school and 8.3% (n= 95) comple ed
11
◦
g ade. Mo e han hal o he pa icipan s (n= 722, 62.9%) has a ull- ime job (40 h
o mo e pe week); 18.8% (n= 216) a e s uden s; 8.1% (n= 93) a e e i ed; 4.4% (n= 51)
wo k pa - ime jobs (16 o 30 h a week) and 44 (3.8%) a e unemployed. Nea ly hal o he
pa icipan s (n= 541; 47.2%) a e ma ied o li ing wi h a companion; 42.7% a e single; 8.7%
(n= 100) a e di o ced, and 16 (1.4%) a e widowed. Mo e han hal (n= 589; 51.3%) ha e
child en. App oxima ely 60% o he pa icipan s indica e ha hei younges child is s ill
unde age.
3.2. Ques ionnai e
The ques ionnai e applied was made a ailable online and included an in o med con-
sen desc ibing he s udy, he aim and opics included and in o ming pa icipan s abou
he conﬁden iali y o hei answe s. Only a posi i e eply would allow o p oceed o o he
i ems ela ed o opics ou o he scope o he p esen a icle ( ac ual knowledge, pe cep-
ions, a i udes, and beha iou s owa ds he i us, i s ansmission, and consequences),
socio-demog aphic in o ma ion, and he ollowing sec ions used in he p esen s udy
(Supplemen a y Ma e ials):
Emo ions: 5-poin Like scale i ems ela ed o he emo ional esponse el in he las
week (calm, ne ous, sad, elaxed, and p eoccupied).
Telewo king and physical ac i i y: 20 i ems ela ed o elewo king (physical condi-
ions, echnological dimensions, and communica ion) and 17 i ems conce ning online and
physical ac i i ies.
4. Resul s
4.1. Adap a ion o Telewo king
The p o essional ac i i ies o mos o he pa icipan s, 81.1% (n= 828), a e compa ible
wi h elewo king, which is exclusi ely conduc ed om home. In e es ingly, 34.2% conside
ha hei p o essional ou ine has no changed, sugges ing ha he e we e su ﬁcien
elemen s in his pe iod o main ain a pe cep ion o cons ancy. This may esul om he
ac ha p o essional ac i i ies, nowadays, ely much mo e on online communica ion
and echnological media han on physically g ounded ac i i ies. Hence, e en hough he
con ex o wo k di e ed, he wo k p ocess i sel , a la ge, did no su e signiﬁcan changes.
An aspec epo ed as being di e en was he ime spen in wo k- ela ed ac i i ies
media ed by ICT. In his ega d, 37.3% o he pa icipan s indica e spending mo e ime
online o using some ICT (e.g., compu e ; elephone); 26.4% indica e a ending o mo e
mee ings and 34.6% o wo k o longe hou s.
Conce ning he ﬁnancial p ac icali ies o his shi , 79.4% o he pa icipan s did no
ecei e any eimbu semen o ex a expenses and 74.5% we e no payed o ex a hou s.
Wha is mo e, a he ime, 18.8% did no e en know i hey would be eimbu sed.
The wo king hou s and ﬁnancial p o isions appea o be a odds wi h he applicable
Eu opean di ec i es on his issue, ega ding, in pa icula , he eimbu semen o any
ex a cos s ela ed o elewo king and communica ions and he app op ia e compensa ion
o ex ao dina y wo king hou s, pa icula ly one ous o hose pa icipan s who epo
wo king longe hou s. Al hough hese sho comings may be unde s ood in he ligh o
he lack o na ional-based egula ion on elewo king, hey s eng hen he need o ein o ce
74
Heal hca e 2021,9, 1151
public policy on his ma e , a EU and na ional le els, as is cu en ly ongoing based on he
independen amewo k o digi aliza ion igh s (see SOC/660–EESC-2020-05278-00-00-AC-
TRA (EN) 2/18).
As conce ns, one o he key ac o s o elewo king—i s physical space—among he
su eyed, 72.2% (n= 594) we e de eloping hei ac i i ies in common and sha ed spaces,
such as he li ing oom (44.6%); he bed oom (19.6%) and he ki chen (4.5%). Only 27.8%
had a speciﬁc oom in he house dedica ed solely o wo k wi hou o e lapping wi h o he
amily dynamics, which is sugges i e ha he majo i y o ou pa icipan s aced one o he
mos p oblema ic issues in elewo king ha is he physical blu ed bounda ies be ween
wo k and home li e [
26
]. This is e en mo e impac ul conside ing ha 47.2% we e in a
ela ionship, 51.3% had child en, o who 61% we e unde 18 and li ing a he house.
Pe cei ed as one po en ial disad an age o elewo king [
22
] he sho comings o
he co-p esence be ween wo k and home we e pa icula ly no ewo hy in he con ex o
COVID-19, gi en ha , due o la ge-scale schools closing, pa en s no only ha e o juggle
wo k and amily li e, bu also manage child en’s home schooling.
In e es ingly, in line wi h wha was ound in [
36
], he oll was el hea ie by he
women. As shown in Table 1 below, when asked abou he emo ions el in he pas
week, men clea ly epo ed mo e posi i e emo ions han women, including eelings o
calm and elaxa ion, and, in con as , women di e ed signiﬁcan ly om men in showing
mo e nega i e emo ions, including ne ousness, sadness, and p eoccupa ion. A one-way
ANOVA (da a no shown) shows ha he e a e signiﬁcan di e ences be ween he g oups
in all he emo ions assessed.
Table 1. Means and S anda d de ia ion o emo ions by gende .
NMSD
Calm Male 346 3.82 1.01
Female 802 3.25 1.04
Ne ousness Male 346 2.25 1.10
Female 802 2.89 1.15
Sadness Male 346 2.60 1.16
Female 802 3.12 1.19
Relaxa ion Male 346 3.06 1.08
Female 802 2.53 1.04
P eocupa ion Male 346 3.28 1.11
Female 802 3.74 0.99
This s eng hens he ﬁndings o [
41
] whe e women epo ed highe psychological
dis ess whe eas men we e appa en ly calme and s onge . These esul s may be inﬂuenced
by he expec ed gende ed display o emo ions bu also due o ex insic p essu es, since, in
gene al, women we e o e all mo e bu dened wi h mo e domes ic and house ca e ac i i ies,
as well as supe ising child en homewo k and didac ic ac i i ies ([
39
,
40
]), wi h an expec ed
nega i e impac on hei wellbeing [36].
The analysis o he emo ional eac ions du ing his pe iod also showed ha , compa ing
all ages, pa icipan s abo e 60 yea s old a e hose ha , albei a a highe isk o pandemic-
ela ed complica ions and mo e a ge ed by o ﬁcial communica ion, we e eeling calme
(M = 3.54;
DP = 1.06
), mo e elaxed (M = 2.77; DP = 1.12), less p eoccupied (M = 3.46;
DP = 1.11
) and less ne ous (M = 2.40; DP = 1.12) han younge indi iduals. Sadness was
he only emo ion equally el by all g oups, app op ia e o he loss and dis up ion el a
hose imes.
The o e all conce n abou olde indi iduals’ heal h ulne abili ies and isk o social
isola ion and highe emo ional impac [
48
] is no co obo a ed in ou sample, wi h younge
indi iduals eeling mo e nega i e emo ions du ing hese imes. This may be ela ed o
he wo k- ela ed unce ain p ocesses and ou comes o he pandemic impac . In e es ingly,
s uden s a e he ones epo ing highe le els o sadness (M = 3.12; DP = 1.13) whe eas
wo ke s (62.9% o ou pa icipan s ha e a ull- ime job and 4.4% a pa ime) epo mo e
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Heal hca e 2021,9, 1151
ne ousness and p eoccupa ion, pa icula ly pa - ime wo ke s, he mos psychologically
dis essed segmen . Nega i e emo ions in wo ke s may also be agg a a ed by he ac
ha 40% o he pa icipan s wo k mo e hou s han be o e a hei wo k places. This esul ,
besides no abiding by gene al egula ions, is a odds wi h he mo e op imis iew o
elewo king as allowing wo ke s o enjoy mo e ee ime o leisu e [
21
] and is, in u n, in
line wi h he isk o p esen eeism [
25
] and o e all nega i e impac s o he psychological
well-being [27].
The wo k spillo e du ing leisu e hou s is no , howe e , he only p oblema ic issue.
The non- e bal o e load o digi al in e ac ion is known o no only ail a mimicking a
heal hie pe sonal expe ience as o os e i edness and i i abili y [
31
]. This is pa icula ly
e idenced in mee ing pla o ms, such as Zoom o Mic oso Teams, in which inc easing
use is also co obo a ed in he p esen s udy. As shown in Figu e 2 below, Zoom was
he mo e equen new ICT pla o m ollowed by Mic oso Teams. The emaining we e
al eady commonly used o communica ing wi h eams and co-wo ke s, especially e-mail
(99.9% o he pa icipan s), ollowed by Wha sApp (56.4%) and Messenge (40.8%). O he
s udies ha e epo ed simila esul s, in which he use o and dependence upon social
media pla o ms, such as Zoom, Mic oso Teams, and Wha sApp, o s ay connec ed o
wo k, educa ion, and social pu poses, ha e seen an exponen ial g ow h in use s du ing
ha ime (e.g., [63,64])
Figu e 2. New ICT ools.
In his ega d, 64.6% o ou pa icipan s epo no using ICT o leisu e, sugges ing
hei use as wo king o u ili a ian ools. One o hese u ili a ian aims, besides wo k, is
online shopping, wi h 45.8% o he pa icipan s epo ing i as a common p ac ice. Fo
23.1%, he equency o on-line pu chasing has inc eased du ing he pandemic ha also
b ough a di e en choice o p oduc s (depic ed in Table 2). Expec edly, conside ing he
measu es o social isola ion and qua an ine a place, he e was a subs an ial inc ease in he
acquisi ion o essen ial goods and oods u s. Gadge s and echnology pu chase also in-
c eased, p obably due o he highe ICT use du ing hese imes o wo k and en e ainmen
pu poses. In e es ingly, he e was a all in all o he o he p oduc s, pa icula ly clo hes.
Table 2. Online pu chases be o e and du ing he pandemic.
Be o e Du ing Pandemic
Essen ial goods and oods u s
26.9% 46.8%
Clo hes 46.5% 9.4%
Cosme ics 5.4% 4.7%
Books 15.8% 7.4%
Gadge s/Technology 5.4% 31.7%
Among he 35.3% who ac ually use ICT o leisu e, he in e es s and ocuses a e
a ied (see Table 3). Physical exe cise classes and apps a e he mo e equen on-line based
ac i i ies, and his in e es and ac ual in es men speaks a ou ably abou he widesp ead
76

Heal hca e 2021,9, 1151
dissemina ion o he impo ance o physical exe cise. This in-home p ac ice e en su passed
he sea ch o en e ainmen -based ac i i ies, as in e ne sea ches, mo ies and TV shows,
and games.
Table 3. Ca ego ies o on-line ac i i ies o leisu e.
N%
Physical exe cise classes and apps 107 27.30%
In e ne sea ches (si es, YouTube) 103 26.40%
Mo ies and shows (Ne ﬂix, HBO) 98 25.10%
Games 71 18.20%
Cul u al ac i i ies (cinema, hea e , conce s) 50 12.80%
Social Media 35 8.90%
4.2. Physical Ac i i y
The in e es in being physically ac i e is no only e idenced by sea ching and pu chas-
ing ela ed physical ac i i y apps and classes online, bu also by he ac ha 70.1% o he
pa icipan s we e al eady ac i e be o e he pandemics, 53.1% p ac icing a speciﬁc spo
and 46.9% ec ea i e and leisu e physical ac i i ies.
E en hough 54.1% epo ha he physical ac i i y dec eased wi h he pandemic,
27.7% we e s ill p ac icing up o 3 imes, 19.9% once a week, and 17.3% up o se en days
a week, which is no so a om he op imal p ac ice sugges ed in [
45
,
57
]. These egula
habi s a e e en mo e impo an conside ing ha 54.2% o ou pa icipan s wo k sea ed
a he compu e wi h he po en ial seden a ism and colla e al psychological p essu e,
s ess, ision p oblems, anxie y, headaches, a igue, sleep diso de s, and skele al muscle
unc ions [
57
]. Fu he mo e, he e was a subs an ial dec ease o younge pa icipan s
(52%) and o pa icipan s abo e 60 yea s old (66%), which s eng hens, e en mo e, he
go e nmen al conce ns in a ge ing his age in pa icula [50].
As expec ed, he e was a shi in he place o physical p ac ice and whe eas 91.7% o
hese ac i i ies we e p ac iced ou side he house wi h he pandemics, only 20.2% o he
pa icipan s we e able o keep ha ou ine. Mo eo e , 79.8% o he pa icipan s epo o
conduc hei physical ac i i ies inside he house, sugges ing an adhe ence o he message
issued by go e nmen s and ein o ced by all media conce ning he p ac ice o physical
ac i i y [
56
]; ICTs, in pa icula , digi al landscapes such as YouTube, social media, and
si es, appea o be o nuclea impo ance in he adop ion o his p ac ice mimicking a eal
li e con ex o physical p ac ice and connec ion [
62
] while 39.3% o he pa icipan s epo
ollowing a egula ou ine nowadays.
Ano he e idence o he compliance o go e nmen al indica ions is he di e ence
be ween he ole o g oup-based ac i i ies o physical exe cise be o e (41.6%) and du ing
he pandemic (3.9%). The e was no change, howe e , in he pe cen age o pa icipan s
exe cising in he company o one mo e pe son. Despi e he o e all equency dec ease, one
may a gue ha wha changed o mos o hem was he adjus men o di e en ou ines
since—up o a highe o lesse deg ee— hey ha e s a ed o p ac ice inside he house and,
mo e o en, alone (73.1% o he pa icipan s in con as wi h 33.8% p io o he pandemic).
The p ac ice o physical exe cise appea s o be mo e equen in pa icipan s wi h a
mas e deg ee (81%) and a PhD (79%) and he leas adop ed by hose wi h a compulso y
educa ion (55.8%). These esul s ollow he widely acknowledged associa ion o physical
exe cise wi h heal h beha iou and be e heal h in gene al [
65
] being pe cei ed by some
au ho s as he single mos impo an and cons an inﬂuence in heal h p ese a ion [66].
On one hand, i is a gued ha o mal educa ion os e s knowledge and alues ela ed
wi h seeking and comp ehending heal h- ela ed in o ma ion as well as ac ing upon i . By
con as , lowe educa ed people a e a highe isk o no engaging in he desi able le els
o physical ac i i y [
67
], which can also be linked o mo e ma e ial p oblems (such as
housing gene al condi ions and a ailable space) o poo heal h expe ienced by olde lowe
educa ed people.
77
Heal hca e 2021,9, 1151
Acco dingly, public heal h communica ion should emphasize beneﬁcial and low
complexi y exe cises (as ae obic home) assessable o all segmen s o he popula ion.
5. Conclusions
5.1. Implica ions
The COVID-19 pandemic has embodied a majo challenge, no only o he heal h
sys em, bu also o se ices, ﬁ ms, wo ke s, and employe s, due o he upswing suddenly
expe ienced by emo e wo king echnologies. The sp ead o elewo king and he use
o echnological pla o ms, in his con ex , has been conside ed essen ial o keep social
dis ancing in wo kplaces and be ween employees and use s/clien s. Gi en he speed o
change in esul o poli ical measu es, se ices, and companies had e y li le ime o pu
oge he a wo k a dis ance plan. E en hough he COVID-19 pandemic and i s mi iga ion
me hods ha e no iced, hese pas mon hs, a g adual dec ease in a numbe o coun ies
conce ning social dis ance, he ex ensi e use o elewo king is expec ed o con inue. As
ecen ly s a ed by he Eu opean Pa liamen Commi ee on Employmen and Social A ai s,
“ he ex ensi e use o elewo k poses a numbe o challenges and equi es a e- hink o
he way wo k is pe o med, coo dina ed, and egula ed” ([
68
], p. 14), bea ing in mind i s
posi i e and nega i e impac s. On his, se e al haza ds o he heal h o elewo ke s ha e
been highligh ed in li e a u e (see in e alia [
69
]), namely physical (e.g., awkwa d pos u es,
epe i i e mo emen s, and long pe iods o con inuous wo k, inc eased a e o physical
inac i i y, and seden a ism) and psychosocial (e.g., sleeping diso de s, wo k- ela ed s ess,
and social isola ion) ones.
I COVID-19 e en s ha e ans o med he wo king condi ions and modiﬁed he
employe -wo ke -use /clien ela ionships, making elewo k unlikely o e u n o p e-
pandemic le els, i is essen ial ha policymake s, se ices, and ﬁ ms ealize he challenges
associa ed wi h his phenomenon, building knowledge o p o ide he basis o change,
imp o emen , and, acco dingly, p omo e gene a i e lea ning om esea ch. This s udy,
conduc ed wi hin he COVID-19 c isis con ex in Po ugal, in ended o g asp speciﬁci ies
o he adap a ion o he lock down and social dis ancing measu es, in wha conce ns
speciﬁcally elewo king condi ions and physical ac i i y p ac ice.
F om his s udy, i is possible o de i e some ﬁndings wi h po en ial implica ions
o he immedia e and pos -pandemic se ings. Fi s , he wo kload and ime spen in
elewo king we e highe han in he physical o ma , i.e., be o e he pandemic. Besides
conﬁ ming he isk o p esen eeism ( o eseen as disad an age o his o ma ) i ein o ces
he need o d a clea and encompassing egula ions and policies p o ec ing he wo ke s
om his p obable spill o e .
Ou esul s also un eiled a p oblem ela ed o he wo ke s’ pe sonal sphe e, ha is, he
lack o a speciﬁc space a home exclusi ely o wo k. The o e lapping o spaces and blu ed
bounda ies be ween wo k and home li e is known o cause en anglemen and con usion as
well as be much mo e demanding in sel -discipline and ime managemen . E en hough
i is ha de o ackle his issue om a public policy iewpoin , i may be mi iga ed a an
o ganiza ional le el: eam-leade s and employees need o be b ie ed and p epa ed in he
mos co-cons uc i e ways o conduc wo k in hese di e en and he e ogeneous condi ions.
Unde a common elewo king policy, ainings, speciﬁc pe o mance c i e ia and weekly
check-ins o gauge hei expe ience and add ess any conce ns should be adop ed. A people-
o ien ed mind se would be beneﬁcial, acknowledging and managing, as much as possible,
he p essing anxie y and s ess ha may esul om hese condi ions.
On he o he hand, his esea ch also sugges s ha women we e subjec ed o mo e
emo ional s ess and impac on psychological wellbeing. This equi es a ailo ed app oach
o aise awa eness abou expec ed gende ed biases while empowe ing women o asse
and deﬁne a mo e balanced dis ibu ion. Gi en ha his is a s uc u al socie al issue, i
may be mo e e ec i e i pu o h and ad oca ed by public o o ganiza ional policies.
The same conce ns apply o he wide use o ICT, also co obo a ed he e, known o
induce a cogni i e o e load wi h a nega i e impac on wellbeing and physical heal h.
78
Heal hca e 2021,9, 1151
E o s in ailo ing occupa ional heal h p og ams and aining should be pu in mo ion and
en o ced by public policies. This may also include he emphasis, al eady no iceable, o he
pe ks and necessi y o physical ac i i y, no longe seen as a hobby bu as a complemen a y
pa o a wo k ou ine. This s udy indica es ha , despi e he di ﬁcul condi ions and
ad e se imes, he e was an e o o con inue o p ac ice physical ac i i ies (also e idenced
in he sea ch o ela ed online classes and apps), which speaks a ou ably o he ecep i i y
o Heal h communica ion and indi idual p edisposi ions.
In addi ion, he lack o eimbu semen o ex a wo k ime o equipmen , a pa wi h
he wo ke s’ unawa eness o hei igh s and wha hey a e en i led o, is indica i e o he
u gency in d a ing egula ions and legisla ions a he Eu opean and na ional le el speci -
ically co e ing elewo k. Conside ing he g adual shi owa ds ﬂexible wo k p ac ices,
hese egula ions should be well-known by he wo ke s.
5.2. Limi a ions o he S udy and Fu u e Resea ch Lines
The p esen s udy has wo main limi a ions o be aken in o accoun and ame he
esul s in e p e a ion. The ﬁ s conce ns i s explo a o y and desc ip i e na u e, eﬂec ed
bo h in he ques ionnai e design and in he analyses conduc ed which a ge ed only a
desc ip ion o gene al condi ions and pa icula beha iou s and p ac ices o he pa icipan s.
The second ega ds he non-p obabilis ic sampling me hod h ough ins i u ional and
pe sonal con ac s, which esul ed in an o e -sampling o highly educa ed indi iduals. In
his ega d, he esul s mus be conside ed in he ligh o his pa icula WEIRD sample
and na ional con ex .
No wi hs anding, conside ing he inc easing ole elewo king is playing in socie y,
his s udy highligh s some pa e ns ha may in o m u he esea ch and policy design
pa icula ly in he analysed con ex , wo h o emphasize ha public policies and co-
ope a ion among social pa ne s a e c ucial o ensu e ha new, e ﬁcien , and wel a e-
imp o ing wo king me hods eme ging du ing he c isis a e main ained and de eloped
once physical dis ancing is o e . To maximize p oduc i i y and wel a e gains inhe en in he
use o mo e widesp ead elewo k, go e nmen s should p omo e in es men s in he physical
and manage ial capaci y o ﬁ ms and wo ke s o elewo k and add ess po en ial conce ns
o he wo ke s’ heal h, well-being, and longe - e m inno a ion ela ed, in pa icula , o
he excessi e downscaling o wo kspaces.
Supplemen a y Ma e ials:
The ollowing a e a ailable online a h ps://www.mdpi.com/a icle/10
.3390/heal hca e9091151/s1, Ques ionnai e.
Au ho Con ibu ions:
Concep ualiza ion, T.F. and G.S.; me hodology, T.F. and G.S.; o mal analysis,
T.F. and G.S.; w i ing—T.F.; G.S. and S.A.C.; p oo eading—T.F.; G.S. and S.A.C. All au ho s ha e
ead and ag eed o he published e sion o he manusc ip .
Funding: This esea ch ecei ed no ex e nal unding.
Ins i u ional Re iew Boa d S a emen :
E hical e iew and app o al we e wai ed o his s udy due
o he absence o isk in da a collec ion o sensible in o ma ion accessed.
In o med Consen S a emen :
In o med consen was ob ained om all subjec s in ol ed in he s udy.
Da a A ailabili y S a emen : No applicable.
Acknowledgmen s:
This wo k was pa ly ﬁnancially suppo ed by he esea ch uni on Go e nance,
Compe i i eness and Public Policy (UIDB/04058/2020) + (UIDP/04058/2020), unded by na ional
unds h ough FCT–Fundaçãopa aaCiência e a Tecnologia.
Conﬂic s o In e es : The au ho s decla e no conﬂic o in e es .
79
Heal hca e 2021,9, 1151
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80
Heal hca e 2021,9, 846
Table 1. Documen s o employmen p omo ion policy o college g adua es.
No. Policy Documen Issuing No. Issuing Depa men Issuing
Da e
P1
No ice on Implemen ing Employmen
Wo k du ing he Pe iod o Epidemic
P e en ion and Con ol
Tianjin People’s O ﬁce
issued (2020) No. 29
Minis y o Human Resou ces and
Social Secu i y o China/Minis y o
Educa ion o China/Minis y o
Finance o China/Minis y o
T anspo a ion o China/Na ional
Heal h Commission
2020.2.5
P2
No ice on Ca ying ou he Na ional
Online Join Rec ui men o 2020 College
G adua es-24365 Campus Rec ui men
Se ice Ac i i ies
Minis y o Educa ion
o China (2020) No. 2
O ﬁce o he Minis y o Educa ion
o China
2020.2.28
P3
No ice on Ca ying ou Employmen and
En ep eneu ship o he 2020 Na ional
College G adua es du ing COVID-19
Minis y o Educa ion
o China (2020) No. 2 Minis y o Educa ion o China 2020.3.4
P4
No ice on Ca ying ou Public
Rec ui men o College G adua es by
Public Ins i u ions du ing COVID-19
Human Resou ces and
Social Secu i y o China
(2020) No. 27
Gene al O ﬁce o he O ganiza ion
Depa men o he CPC Cen al
Commi ee o China/Gene al O ﬁce o
he Minis y o Human Resou ces and
Social Secu i y o China
2020.3.11
P5
Sugges ions on S eng hening and
S abilizing Employmen du ing
COVID-19
O ﬁce o he S a e
Council o China (2020)
No. 6
O ﬁce o he S a e Council o China
2020.3.18
P6
No ice on Implemen ing Some Voca ional
Qualiﬁca ions “Fi s Employed hen
Passed he Exam”
Human Resou ces and
Social Secu i y o China
(2020) No. 24
Minis y o Human Resou ces and
Social Secu i y o China/Minis y o
Educa ion o China/Minis y o
Jus ice o China/Minis y o
Ag icul u e and Ru al A ai s o
China/Minis y o Cul u e and
Tou ism o China/Na ional Heal h
Commission o China/Na ional
In ellec ual P ope y O ﬁce o China
2020.4.21
P7
No ice on Holding he 2020 Na ional
College G adua e Employmen Ne wo k
Alliance Rec ui men Week
Minis y o Educa ion
o China (2020) No. 7
Minis y o Educa ion o he People’s
Republic o China
2020.4.23
P8No ice on Ca ying ou he Pionee base
o En ep eneu ship and Employmen
Na ional De elopmen
and Re o m
Commission o China
(2020) No. 310
Gene al O ﬁce o he Na ional
De elopmen and Re o m
Commission o China/Gene al O ﬁce
o he S a e-owned Asse s Supe ision
and Adminis a ion Commission o
he Minis y o Educa ion o
China/Gene al O ﬁce o he Minis y
o Human Resou ces and Social
Secu i y o China
2020.4.24
P9
No ice on Na ional SME Online
Rec ui men o College G adua es in
100 Days
Minis y o Indus y
and In o ma ion
Technology o China
(2020) No. 179
P o incial Depa men o Indus y
and In o ma ion Technology o
China/P o incial Depa men o
Educa ion o China/P o incial
Depa men o Human Resou ces and
Social Secu i y o China
2020.4.27
P10
“No ice on Public Rec ui men o
Kinde ga en Teache s in P ima y and
Seconda y Schools in 2020
Human Resou ces and
Social Secu i y o China
(2020) No. 28
Minis y o Human Resou ces and
Social Secu i y o China/Minis y o
Educa ion o China/Cen al Planning
O ﬁce o China/Minis y o Finance
o China
2020.5.9
87

Heal hca e 2021,9, 846
Table 1. Con .
No. Policy Documen Issuing No. Issuing Depa men Issuing
Da e
P11
No ice on Implemen a ion o he “Th ee
Suppo s and One Suppo ” Plan o
College G adua es in 2020
Human Resou ces and
Social Secu i y o China
(2020) No. 57
Gene al O ﬁce o he Minis y o
Human Resou ces and Social Secu i y
o China/Gene al O ﬁce o he
Minis y o Finance o China
2020.5.19
P12
No ice on Encou aging Scien iﬁc Resea ch
P ojec s o Abso b College G adua es
Minis y o Science and
Technology o China
(2020) No. 132
Minis y o Science and Technology o
China/Minis y o Educa ion o
China/Minis y o Human Resou ces
and Social Secu i y o China/Minis y
o Finance o China/Chinese
Academy o Sciences/Na u al Science
Founda ion o China
2020.5.27
P13
No ice on Fu he De elopmen o
Resea ch Assis an Posi ions in Colleges
and Uni e si ies o Abso b G adua e
Employmen
Minis y o Educa ion
o China (2020) No. 23
O ﬁce o he Minis y o Educa ion
o China 2020.6.4
P14
No ice on Guiding and Encou aging
College G adua es o Wo k and S a
Business in U ban and Ru al
Communi ies
Human Resou ces and
Social Secu i y o China
(2020) No. 53
O ganiza ion Depa men o he Pa y
Commi ee o each ci y
(p e ec u e)/Ci iliza ion O ﬁce o
China/Ci il A ai s Bu eau o
China/Educa ion Adminis a i e
Depa men o China/Finance Bu eau
o China/Human Resou ces and
Social Secu i y Bu eau o
China/Heal h and Heal h Commi ee
o China
2020.6.22
P15
No ice on P ecise Assis ance o
Employmen o College G adua es om
Poo Families in 52 Po e y Coun ies”
Minis y o Educa ion
o China (2020) No. 21
Gene al O ﬁce o he Minis y o
Educa ion o China/Gene al O ﬁce o
he Minis y o Human Resou ces and
Social Secu i y o China/Gene al
Depa men o he Po e y Alle ia ion
O ﬁce o he S a e Council o China
2020.7.2
P16
Sugges ions on Allowing Medical College
G adua es o Exemp om Examina ion
o Apply o P ac icing Regis a ion o
Ru al Doc o s
Na ional Heal h
Commission o China
(2020) No. 11
Na ional Heal h Commission o China
2020.7.6
Based on policy ex , his pape uses ROST CM [
22
,
23
] so wa e o p ep ocess he
policy ex , such as wo d segmen a ion and keywo d equency s a is ics, in o de o
ex ac he key con en om he policy documen . The speciﬁc p ocess is as ollows:
ﬁ s , he policy ex is segmen ed, hen he wo d equency o he documen a e wo d
segmen a ion is anked, and ﬁnally he wo d segmen a ion esul s a e so ed acco ding o
he wo d equency om high o low. The esul s a e shown in Table 2. In addi ion, he
Ucien so wa e was used o build a co-occu ence ne wo k o he documen s a e wo d
segmen a ion, and he esul s a e shown in Figu e 2. Each node in he ne wo k ep esen s a
keywo d, and i he e is a line be ween nodes, he keywo ds ha e a symbio ic ela ionship.
A he same ime, nodes a e displayed acco ding o he keywo d cen ali y. I he keywo d
has highe cen ali y, he keywo d equen ly appea s oge he wi h o he keywo ds in he
ne wo k [24].
88
Heal hca e 2021,9, 846
Table 2.
S a is ics o keywo d equency in employmen p omo ion policy documen s o college
g adua es.
Keywo d F equency Keywo d F equency
employmen 1328 esou ce 678
g adua e 1322 sa egua d 676
college 1314 implemen 575
ec ui men 1166 socie y 474
se ice 1130 scien iﬁc esea ch 371
company 1120 p og am 271
en ep eneu ship 1111 s eng hen 168
posi ion 890 epidemic 166
o ganiza ion 887 pe sonnel 166
en e p ise 882 policy 164
depa men 781 g ass oo s 88
Figu e 2. Co-ci a ion ne wo ks o keywo d in employmen p omo ion policy documen s o college g adua es.
I can be seen om he keywo d equency dis ibu ion and keywo d co-ci a ion
ne wo ks o he a o emen ioned policy documen s ha “employmen ”, “se ice”, and
“posi ion” ank ﬁ s among he high- equency wo ds. This is di e en om he p e ious
si ua ion o college g adua es. The COVID-19 has led uni e si ies and companies o cancel
o ﬂine job ai s o he class o 2020, which a e he main job oppo uni ies o esh g adua es.
The e o e, du ing COVID-19, he mos impo an hing o he go e nmen is o mobilize all
uni s o implemen online employmen se ices, expand employmen channels and inc ease
employmen oppo uni ies. F om he wo high- equency wo ds “en ep eneu ship” and
“g ass- oo s le el”, we can see ha in o de o inc ease he employmen oppo uni ies o
college g adua es, he go e nmen has epea edly men ioned encou aging, suppo ing
and guiding g adua es o ﬁnd jobs a he g ass- oo s le el, s abilizing he en i onmen
o inno a ion and en ep eneu ship, and gi ing ull play o he impo an ole o “mass
en ep eneu ship and inno a ion” in suppo ing employmen .
4.2. E alua ing Employmen P omo ion Policy Documen s o College G adua es Based on
PMC Model
A p esen , he mo e ad anced in e na ional policy ex e alua ion me hod is he
PMC Index E alua ion Model es ablished by Es ada [
25
]. This model belie es ha e -
89
Heal hca e 2021,9, 846
e y hing is cons an ly in mo ion and in e connec ed, so any ele an a iable canno be
igno ed. I s inno a ion is ha i uses bina ydigi s 0 and 1 o balance all a iables and
emphasizes ha he numbe and weigh o a iables should no be limi ed, so ha he
ad an ages and disad an ages and in e nal consis ency o a policy can be analyzed om
a ious dimensions [26]. Mos exis ing policy e alua ion me hods ha e p oblems such as
s ong subjec i i y and low accu acy. Howe e , he PMC index model me hod can la gely
a oid subjec i i y and imp o e accu acy because i ob ains aw da a h ough ex mining.
In addi ion, he e ec i eness o he PMC model has been e iﬁed in he li e a u e [
25
].
In he policy analysis in his pape , he PMC index model akes a iables in o ex ensi e
conside a ion, which no only can comp ehensi ely analyze he me i s and deme i s o a
policy, bu also has he ad an ages o index aceabili y and g ade iden iﬁca ion, and scien-
iﬁcally quan iﬁes he consis ency le el o each policy om di e en dimensions. The e o e,
his pape in oduces he PMC index model o quan i a i ely e alua e he employmen
p omo ion policy o college g adua es unde COVID-19 and ob ains he key poin s o
he policy con en om he ou s anding policy documen s wi h a PMC index sco e o
9–10. Gene ally, he es ablishmen o a PMC index model includes he ollowing s eps:
(1) es ablishing a PMC index e alua ion index sys em, (2) es ablishing a mul i-inpu -ou pu
able, and (3) calcula ing wole el a iable alues and PMC index.
4.2.1. Classi ying he Va iables and Se ing Pa ame e s o PMC Index Model
Re e ing o Es ada and he exis ing li e a u es [
27
–
29
] and combining wi h he
speciﬁc cha ac e is ics o college g adua es’ employmen p omo ion policy, his pape
es ablishes 10 ﬁ s -le el a iables and 66 s-le el a iables. The esul s a e shown in Table 3.
Table 3. PMC e alua ion a iables o employmen p omo ion policy o g adua es.
Fi s -Le el Va iables Second-Le el
Va iables No.
Second-Le el Va iables
Name
Second-Le el
Va iables No.
Second-Le el Va iables
Name
Na u e o X1policy
X1:1 supe ision X1:2 suppo
X1:3 ad isemen X1:4 encou age
X1:5 guide
Time o X2policy X2:1 ansi ion pe iod X2:2 sho e m
X2:3 his yea
Field o X3policy
X3:1 economy X3:2 public managemen
X3:3 alen X3:4 social secu i y
X3:5 echnology X3:6 ins i u ion
Func ion o X4policy
X4:1 expand demand X4:2 no ma i e guidance
X4:3 s eng hen p o ec ion X4:4 ins i u ional cons ain s
X4:5 op imize sys em
Objec i e o X5policy
X5:1 en e p ise X5:2 college g adua es
X5:3 college X5:4
all p o inces, ci ies,
au onomous egions, and
municipali ies di ec ly unde
he Cen al Go e nmen
X5:5 di ec ly subo dina e agency X5:6 key a eas o he epidemic
X5:7 minis ies and commissions o
he S a e Council
Con en o X6policy
X6:1 esump ion o wo k and
p oduc ion X6:2 employmen subsidy
X6:3 employmen se ice X6:4 encou age employmen and
en ep eneu ship
X6:5 s able employmen X6:6
b oaden employmen channels
X6:7 s eng hen aining X6:8 encou age g ass oo s wo k
X6:9 accu a e employmen
assis ance
90
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Table 3. Con .
Fi s -Le el Va iables Second-Le el
Va iables No.
Second-Le el Va iables
Name
Second-Le el
Va iables No.
Second-Le el Va iables
Name
Issuing agency o X7
policy
X7:1 Minis y o Human Resou ces
and Social Secu i y X7:2 Minis y o Educa ion
X7:3 Minis y o Finance X7:4 T anspo a ion Depa men
X7:5 Na ional Heal h Commission X7:6 p o inces and ci ies
X7:7
Local and subo dina e colleges
and uni e si ies X7:8 Gene al O ﬁce o he Cen al
O ganiza ion Depa men
X7:9
Depa men o Jus ice (Bu eau)
X7:10
Depa men o Ag icul u e and
Ru al A ai s (Ag icul u e,
Animal Husband y and
Ve e ina y Medicine, Fishe y)
(Bu eau, Commission)
X7:11 Depa men o Cul u e and
Tou ism (Bu eau) X7:12
In ellec ual P ope y O ﬁce
(In ellec ual P ope y
Managemen Depa men )
X7:13 SASAC
Incen i es o X8policy
X8:1 employmen subsidy X8:2 job c ea ion
X8:3 ax incen i es X8:4 alen incen i e
X8:5 online employmen X8:6 mul i-channel employmen
X8:7
incen i es o p ima y se ices
X8:8 sel -employed
X8:9 skills T aining X8:10 employmen guidance se ice
X8:11 encou age eaching X8:12 employmen assis ance
X8:13 lowe he ba ie s o
employmen
E alua ion o X9policy
X9:1 clea objec i e X9:2 easible plan
X9:3 su ﬁcien e e ence X9:4 de ailed planning
X9:5 encou age employmen
Publica ion o X10
policy —
The weigh s o he second-le el a iables in Table 3 a e se o he same alue, and all
he pa ame e alues o he second-le el a iables a e se o bina ydigi s 0 and 1. I he
con en o he policy documen in ol es he meaning o he second-le el a iables, i is
assigned he alue 1; o he wise, i is 0.
4.2.2. Cons uc ing Inpu -Ou pu Table
The inpu -ou pu able is a da a analysis amewo k ha can s o e a la ge amoun
o da a and use mul idimensional measu emen o a single a iable. I is composed o
nume ous ﬁ s -le el a iables and second-le el a iables ha a e no es ic ed by a iables.
The ﬁ s -le el a iables ha e no ﬁxed o de and a e independen o each o he , and he
weigh s o he second-le el a iables a e equal [30], as shown in Table 4.
The second-le el a iables’ alues a e assigned acco ding o he keywo ds ob ained
in Sec ion 4.1. When he policy ex da a con ains he keywo ds co esponding o he
second-le el a iables, he alue is assigned o 1; o he wise, i is 0. Compa ed wi h he
subjec i i y o expe sco ing, his me hod is mo e objec i e and scien iﬁc.
91
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Table 4. Inpu -ou pu able.
Fi s -Le el Va iables Second-Le el Va iables
X1X1:1 X1:2 X1:3 X1:4 X1:5
X2X2:1 X2:2 X2:3
X3X3:1 X3:2 X3:3 X3:4 X3:5
X4X4:1 X4:2 X4:3 X4:4 X4:5
X5X5:1 X5:2 X5:3 X5:4 X5:5 X5:6 X5:7
X6X6:1 X6:2 X6:3 X6:4 X6:5 X6:6 X6:7
X6:8 X6:9
X7X7:1 X7:2 X7:3 X7:4 X7:5 X7:6 X7:7
X7:8 X7:9 X7:10 X7:11 X7:12 X7:13
X8X8:1 X8:2 X8:3 X8:4 X8:5 X8:6 X8:7
X8:8 X8:9 X8:10 X8:11 X8:12 X8:13
X9X9:1 X9:2 X9:3 X9:4 X9:5
X10 —
4.2.3. Calcula ing PMC Index
The PMC index o he policy documen s in Table 1 is calcula ed below. The calcula ion
me hod is as ollows:
Xi:j∼n, (1)
iis ﬁ s -le el a iables; jis second-le el a iables, i,j= 1,2,3,4,5. . . . ∞.
Xi=∑n
j=1
Xi:j
n, (2)
nis he amoun o second-le el a iables, n= 1,2,3,4,5. . . . ∞.
PMC =X1(∑5
a=1X1:a
5)+X2(∑3
b=1X2:a
3)+X3(∑5
c=1X3:c
5)+X4(∑5
d=1X4:d
5)
+X5(∑7
e=1X5:e
7)+X6(∑9
=1
X6:
5)+X7(∑13
g=1
X7:g
5)+X8(∑13
h=1X8:h
5)
+X9(∑5
k=1X9:k
5)+X10
(3)
Fi s , de e mine he alue o he second-le el a iable X
i:j
acco ding o Fo mula (1), hen
calcula e he alue o each i s -le el a iable acco ding o Fo mula (2), and inally b ing
each i s -le el a iable in o Fo mula (3) o calcula e he PMC index o di e en policies. The
PMC index e alua ion c i e ia can be ob ained om he li e a u e [
21
]:
9–10 poin s
(pe ec
le el), 7–8.99 poin s (excellen le el), 5–6.99 poin s (accep able le el), 0–4.99 poin s (bad
le el). This me hod ob ains he anking and a ing o he PMC index o he employmen
p omo ion policy o college g adua es, and he esul s a e shown in Table 5.
Table 5. PMC index o employmen p omo ion policy documen s o college g adua es.
X1X2X3X4X5X6X7X8X9X10 PMC
Index Ranking Dep ession
Index Ra ing
P11 0.33 0.5 0.4 0.71 0.56 0.38 0.23 0.4 1 5.51 5 4.49 accep able
P20.4 0.67 0.33 0.4 0.43 0.22 0.23 0.08 1 1 4.76 9 5.24 bad
P31 0.67 0.67 1 0.43 0.78 0.15 0.69 1 1 7.39 2 2.61 pe ec
P40.8 0.67 0.33 0.6 0.43 0.56 0.23 0.31 0.6 1 5.53 4 4.47 accep able
P51 1 1 0.8 0.86 0.89 0.15 0.69 0.6 1 7.99 1 2.01 pe ec
P60.4 0.67 0.5 0.4 0.29 0.22 0.54 0.23 0.8 1 5.05 8 4.95 accep able
P70.2 0.33 0.33 0.2 0.43 0.22 0.15 0.15 0.6 1 3.61 15 6.39 bad
P80.6 0.33 0.33 0.8 0.71 0.44 0.23 0.46 0.8 1 5.7 3 4.3 accep able
P90.4 0.33 0.17 0.4 0.29 0.33 0.08 0.08 1 1 4.08 14 5.92 bad
P10 0.4 0.33 0.5 0.4 0.29 0.33 0.31 0.23 0.8 1 4.59 11 5.41 bad
P11 0.8 0.33 0.5 0.4 0.29 0.33 0.23 0.23 1 1 5.11 7 4.89 accep able
P12 0.6 0.33 0.33 0.4 0.29 0.22 0.31 0.15 1 1 4.63 10 5.37 bad
P13 0.6 0.33 0.33 0.4 0.29 0.22 0.31 0.15 0.6 1 4.23 12 5.77 bad
P14 0.6 0 1 0.8 0.29 0.22 0.38 0.38 0.6 1 5.27 6 4.73 accep able
P15 0.4 0 0.17 0.4 0.43 0.44 0.23 0.23 0.8 1 4.1 13 5.9 bad
P16 0.6 0 0.17 0.4 0.43 0.22 0.08 0.15 0.2 1 3.25 16 6.75 bad
a e age
0.61 0.39 0.45 0.51 0.43 0.39 0.25 0.28 0.74 1
92

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F om he e alua ion esul s in Table 5, i can be seen ha among he 16 college g adua e
employmen p omo ion policies, eigh o he policy e alua ion esul s a e accep ablele el o
abo e, accoun ing o 50%, among which wo a e pe ec , and he policy con en con ained
in he pe ec policy documen is mo e comp ehensi e. The a ge audience is wide , and
he s eps in ol ed in he implemen a ion measu es a e mo e de ailed. The e o e, in o de o
ex ac he key poin s in he policy documen s, he con en s o he P
3
and P
5
pe ec -le el policy
documen s a e selec ed and summa ized. Due o he di e si y o he measu es p oposed in
he policy and hei di e en ocuses, he con en o he policy is di ided in o ou a eas: (1)
Inc ease he oppo uni ies o u he educa ion and educe he numbe o esh g adua es
who a e in u gen need o employmen . (2) B oaden employmen in o ma ion ci cula ion
channels, and guide uni e si ies and colleges o ca y ou ex ensi e online employmen . (3)
P o ide employmen subsidies, lowe employmen es ic ions, alle ia e employmen anxie y
o ecen g adua es, and imp o e employmen bene i s o ecen g adua es. (4) Inc ease
posi ion and inc ease labo demand. Acco ding o he abo e ou aspec s, he employmen
p omo ion policy measu es o college g adua es can be di ided in o ou ca ego ies: channel
measu es, ans e ence measu es, subsidy measu es, and posi ion measu es.
5. Analyzing Social E ec s on Employmen P omo ion Policies o College G adua es
As a eﬂec ion o public sen imen and public opinion, online public opinion no
only mani es s i s inﬂuence on majo de elopmen s, bu also pene a es in o he poli ical
le el, becoming an impo an channel o he go e nmen o lis en o and unde s and
public opinion. In o de o dig ou he public’s a i ude and esponse o he o ﬁcial employ-
men p omo ion policy unde he COVID-19 pandemic, he co esponding opic commen
in o ma ion on he Weibo is c awled, and social implemen a ion e ec o employmen
p omo ion policy is analyzed based on he commen s.
5.1. Acqui ing and P ep ocessing Da a
5.1.1. Acqui ing Da a
This pape sea ches ela ed opics o 4 kinds o measu es on Weibo and selec s he
15 opics discussedmos equen ly as he da a c awling objec s. Each opic is shown in
Table 6
.
Table 6. Rela ed Weibo opics.
Policy Weibo Topic
Channel measu es
24.356 all-day online campus employmen se ice
Encou age mul iple me hods such as webcas ing
Single assis ance be ween domes ic colleges and Hubei colleges
T ans e ence measu es
En ollmen o pos g adua e s uden s inc eased by 189,000
Expand he scale o en ollmen o pos g adua es and unde g adua es
Expand he pos g adua e en ollmen o e i ed soldie s in college
Subsidy measu es
P o ide employmen subsidies o college g adua es in many places
The highes awa d o inno a ion and en ep eneu ship o Tianjin college
g adua es is 300,000 RMB
Find a job wi hin wo yea s and go h ough he employmen p ocedu es
acco ding o he cu en e m
G adua es can keep hei household egis a ion ﬁles in he school o wo
yea s
Posi ion measu es
S a e-owned en e p ises expand he en ollmen o college g adua es his yea
and nex wo yea s
Expand he ec ui men o p ima y and seconda y school eache s
Implemen “ﬁ s ec ui ed, hen passed he exam”
Special pos eache s plan o inc ease ec ui men by 5000
De elop esea ch assis an posi ion o a ac college g adua es
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This pape awls he ela ed Weibo commen s on 15 opics. The awled con en
includes he publishe ID, he con en o he commen , commen ime, commen e ID,
he numbe o ollowe s, he numbe o subsc ibe s, and Weibo numbe . This pape uses
py hon o ob ain a o al o 65,487 pos s, including 9596 pos s o channel measu es opics,
17,003 pos s o ans e ence measu es opics, 7671 pos s o subsidy measu es opics, and
28,849 pos s o posi ion measu es opics. The da a o ma is shown in Figu e 3.
Figu e 3. Da a o ma .
5.1.2. Da a Cleaning
Because in alid da a and inco ec da a ine i ably appea in he awling p ocess,
hese da a a e a ely u ilized in he analysis p ocess o cause la ge e o s in he esul s,
hus hey need o be dele ed. Da a cleaning mainly dele es epea edly collec ed da a,
epea ed exp ession wo ds, sho e sen ences, meaningless, o unclea sen ences. A e
da a cleaning, a o al o 61,311 alid pos s we e ob ained.
5.1.3. Wo d Segmen a ion and Wo d F equency S a is ics
As he con en o he commen s a e all in Chinese, he Jieba Chinese wo d segmen a-
ion package [
31
] is used o pe o m wo d segmen a ion on he Weibo commen s in he
Py hon en i onmen and emo e s op wo ds ha canno ep esen ex cha ac e is ics.
Because he esea ch objec o his pape is he employmen policy o college g adua es
unde COVID-19 pandemic, he nouns ha appea equen ly in he documen a e wo d
segmen a ion a e “s uden , socie y, employmen ”, e c., such wo ds a e mo e neu al and
ha e less meaning o wo d equency analysis. The e o e, his ype o wo d is also added
o he s op wo d dic iona y. On his basis, he op 100 e ec i e high- equency wo ds
a e so ed ou as ollows: “ eache ”, “quo a”, “pos g adua e”, “epidemic”, “ esh g adu-
a e”, “ ac ional line”, “condi ion”, “ﬁle”, “p e ious g adua e”, “ ull- ime”, “employmen
a e”, “labo o ce”, “ alen ”, “young people”, “mas e ”, “quali y”, “ci il se an ”, “pa -
ime”, “housing p ice”, “Wuhan”, “wo kload”, “ esea ch assis an ”, “p opo ion”, “no mal
majo ”, “doc o ”, “Guangdong”, “qualiﬁca ion”, “w i en examina ion”, “special pos
eache ”, “Chongqing”, “s uden sou ce”, “ma hema ics”, “college p omo ion”, “uni ”,
“age”, “college”, “ h eshold”, “p elimina y examina ion”, “junio college s uden ”, “o i-
gin”, “Sichuan”, “ene gy”, “household egis a ion”, “ e-examina ion”, “unemploymen
a e”, “poo s uden ”, “wel a e”, “en e p ise”, “a ea”, “le el”, “accomplishmen ”, “bache-
lo ”, “doc o al s uden ”, “Shandong”, “Henan”, “junio college”, “ egis e ed esidence”,
“ ea men ”, “Beijing”, “elemen a y school”, “sala y”, “subsidy”, “uni e si y”, “head
eache ”, “in e iew”, “ ipa i e ag eemen ”, “ oca ional school”, “con ac ”, “ u al a ea”,
“p eschool educa ion”, “abili y”, “Anhui”, “ ownship”, “unde g adua e”, “Shanghai”,
“ egion”, “ci y”, “second deg ee”, “whole coun y”, “go e nmen o ﬁce”, “hospi al”, “ins i-
u ion”, “kinde ga en”, “domicile”, “Chinese”, “a ”, “enginee ing”, “nu se”, “p essu e”,
“ag eemen ”, “expe ience”, “kinde ga en eache ”, “counselo ”, “down own”, “Tianjin”,
“o he p o ince”, “music”, “English”, “news”, “coun y own”.
94
Heal hca e 2021,9, 846
5.2. Cons uc ion o E alua ion Model o Suppo ing Policy Measu es
An e alua ion model o suppo ing policy measu es is cons uc ed he e o e alua e
and analyze he public suppo deg ee o he ou ypes o measu es summa ized by
he abo e PMC index model o s udy he social e ec s o he implemen a ion o he
employmen p omo ion policy o college g adua es.
5.2.1. Cons uc ing E alua ion Dimension
The deg ee o suppo o policy measu es needs o be analyzed om mul iple di-
mensions, including he heo e ical goals o he policy measu es, he people’s expec a ions
o he policy measu es, and he speciﬁc implemen a ion me hods o he policy measu es.
Mos o he p e ious s udies analyzed he policy suppo deg ee om one dimension ( he
heo e ical objec i es o he policy [
32
], he expec a ions o he masses [
33
,
34
], he policy
means [
35
], e c.). The co e age o he policy is ela i ely na ow and lacks objec i i y,
which a ec s he scien iﬁc s a is ical esul s. In o de o imp o e he c edibili y o he
esea ch esul s, his pape e e s o he a ious e alua ion dimensions adop ed by he
exis ing esea ch and edeﬁnes he e alua ion dimensions. S a ing om mul iple dimen-
sions, i analyzes he deg ee o public suppo o a ious measu es o college g adua e
employmen p omo ion policies. The dimensions a e shown in Table 7.
Table 7. E alua ion dimension.
E alua ion Dimension Commen s
Dimension Deﬁni ion
Theo e ical objec i es
The heo e ical e ec o be
achie ed a he go e nmen
le el unde he p ese
expec a ions o
policy measu es
Since he epidemic is so se e e
his yea , i is necessa y o
in oduce policies o ensu e
employmen .
Expec a ions o he masses
Expec ed e ec s o policy
measu es a he public le el
Wi h pos g adua e en ollmen
expansions, he g adua e deg ee
will be wo hless in he u u e.
Implemen a ion means
Speciﬁc implemen a ion
me hods and p ocesses o
policy measu es
The policy was issued oo la e, he
school has al eady sen he
ﬁles back.
Ta ge g oups The main body o
policy measu es
Hope his policy is no jus o
esh g adua es.
5.2.2. Cons uc ing Commen Topic Iden iﬁca ion Sys em
As ne izens o en e alua e policy measu es om di e en posi ions and pe spec i es,
each commen may co espond o di e en e alua ion dimensions. This pape uses he
amewo k seman ic dic iona y ma ching me hod, akes he policy e iew subjec wo d
dic iona y as he label sys em, and comple es he iden iﬁca ion o he co esponding
dimensions by ex ac ing and ma ching he e alua ion wo ds o commen s. Among hem,
he policy e iew opic iden iﬁca ion wo d dic iona y is mainly gene a ed based on he
equency o keywo d in he commen s combined wi h manual selec ion. Due o he la ge
numbe o iden iﬁed wo ds, he seman ic logic induc ion me hod is used o summa ize and
eﬁne i . Six een hemes a e gene a ed: “na ional condi ion”, “human esou ce”, “wo k
ea men ”, “wo k in ensi y”, “lea ning o m”, “school oll”, “employmen ag eemen ”,
“employe ”, “posi ion”, “examina ion”, “en ollmen ”, “ egion”, “educa ion”, “subjec ”,
“s uden ype”, and “applicable condi ion”. Combining he e alua ion dimension sys em
cons uc ed in Table 7 and he co esponding 16 hemes wi h 4 e alua ion dimensions,
a commen opic iden iﬁca ion sys em is ob ained as shown in Table 8. This can a oid
seman ic con usion caused by a la ge numbe o opic wo ds, he eby imp o ing he da a
s uc u e and cla i ying he e alua ion dimension o which he ex belongs.
95
Heal hca e 2021,9, 846
Table 8. Commen opic iden iﬁca ion sys em.
Dimension Theme Iden iﬁca ion Wo d
Theo e ical objec i es Na ional condi ion employmen a e, unemploymen a e,
epidemic, housing p ice
Human esou ce labo o ce, alen , young people, quali y
Expec a ions o he masses Wo k ea men sala y, ea men , subsidy, wel a e
Wo k in ensi y p essu e, wo kload, ene gy
Implemen a ion means
Lea ning o m ull- ime, pa - ime
School oll ﬁle, s uden sou ce, egis e ed esidence,
o igin, household egis a ion, domicile,
Employmen
ag eemen ag eemen , ipa i e ag eemen , con ac
Employe
kinde ga en, en e p ise, uni e si y,
go e nmen o ﬁce, hospi al, ins i u ion,
oca ional school, elemen a y school,
college, uni
Posi ion
nu se, kinde ga en eache , eache , ci il
se an , counselo , head eache , esea ch
assis an , special pos eache
Examina ion w i en examina ion, in e iew,
p elimina y examina ion, eexamina ion
En ollmen quo a, p opo ion
Ta ge g oups
Region
Shandong, Wuhan, Beijing, u al a ea,
Chongqing, Sichuan, Guangdong, Anhui,
Tianjin, a ea, Shanghai, Henan, whole
coun y, o he p o ince, ci y, down own,
egion, coun y own, ownship
Educa ion bachelo , junio college, Doc o , Mas e ,
second deg ee, college p omo ion
Subjec
no mal majo , ma hema ics, music,
Chinese, English, news, a , enginee ing,
p eschool educa ion
S uden ype
esh g adua e, poo s uden , doc o al
s uden , pos g adua e, unde g adua e,
junio college s uden , p e ious g adua e
Applicable
condi ion
age, qualiﬁca ion, h eshold, condi ion,
expe ience, abili y, accomplishmen ,
ac ional line, le el
The abo e-men ioned commen opic iden iﬁca ion sys em is used o map commen s
o di e en e alua ion dimensions. By iden i ying and ma ching commen s, a o al o
51,567 pieces o commen s ela ed o 4 e alua ion dimensions we e ex ac ed. The speciﬁc
esul s a e shown in Table 9.
96
Heal hca e 2021,9, 846
in he u u e, we will collec da a om all coun ies, conduc a ge ed esea ch, and
gi e co esponding sugges ions.
Au ho Con ibu ions:
T.C. desc ibed he p oposed amewo k and w o e he whole manusc ip ;
J.R. implemen ed he simula ion expe imen s; L.P. and J.F. collec ed da a; J.Y. and G.C. e ised he
manusc ip . All au ho s ha e ead and ag eed o he published e sion o he manusc ip .
Funding:
This esea ch is suppo ed by he Na ional Social Science Founda ion o China (G an No.
20BTQ059), he P ojec o China (Hangzhou) C oss-bo de E-comme ce College (No.2021KXYJ07),
he Key P ojec o Zhejiang P o ince Educa ion Science Planning in 2021 (G an No. 2021SB103),
he Gene al Scien iﬁc Resea ch P ojec o P o essional Deg ee Pos g adua es o Zhejiang Educa ion
Depa men in 2020 (G an No. Y202045139), he Scien iﬁc Resea ch P ojec o Zhejiang Educa ion
Depa men (G an No. Y201737899), he Con empo a y Business and T ade Resea ch Cen e and
Cen e o Collabo a i e Inno a ion S udies o Mode n Business o Zhejiang Gongshang Uni e si y
o China (G an No. 14SMXY05YB), as well as he Cha ac e is ic & P eponde an Discipline o Key
Cons uc ion Uni e si ies in Zhejiang P o ince (Zhejiang Gongshang Uni e si y-S a is ics).
Ins i u ional Re iew Boa d S a emen : No applicable.
In o med Consen S a emen :
In o med consen was ob ained om all subjec s in ol ed in he s udy.
Da a A ailabili y S a emen :
The da a used o suppo he ﬁndings o his s udy a e a ailable om
he co esponding au ho upon eques .
Conﬂic s o In e es : The au ho s decla e no conﬂic o in e es .
Re e ences
1.
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104
heal hca e
A icle
Assessing he Knowledge, A i udes and P ac ices o COVID-19
among Qua an ine Ho el Wo ke s in China
Yi-Man Teng 1,†, Kun-Shan Wu 2,*,†, Wen-Cheng Wang 3and Dan Xu 1
Ci a ion: Teng, Y.-M.; Wu, K.-S.;
Wang, W.-C.; Xu, D. Assessing he
Knowledge, A i udes and P ac ices
o COVID-19 among Qua an ine
Ho el Wo ke s in China. Heal hca e
2021,9, 772. h ps://doi.o g/
10.3390/heal hca e9060772
Academic Edi o s: Thomas Ga a an,
Edua do Toméand Ana Dias
Recei ed: 26 May 2021
Accep ed: 17 June 2021
Published: 21 June 2021
Publishe ’s No e: MDPI s ays neu al
wi h ega d o ju isdic ional claims in
published maps and ins i u ional a ﬁl-
ia ions.
Copy igh : © 2021 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license (h ps://
c ea i ecommons.o g/licenses/by/
4.0/).
1
College o Mode n Managemen , Yango Uni e si y, Fuzhou 350015, China; [email p o ec ed] (Y.-M.T.);
[email p o ec ed] (D.X.)
2Depa men o Business Adminis a ion, Tamkang Uni e si y, Taipei 251301, Taiwan
3College o Inno a ion and En ep eneu ship Educa ion, Yango Uni e si y, Fuzhou 350015, China;
[email p o ec ed]
*Co espondence: [email p o ec ed]
† Equal ﬁ s au ho ship.
Abs ac :
Du ing he pandemic, qua an ine ho el wo ke s ace a highe isk o in ec ion while hey
hos qua an ine gues s om o e seas. This s udy’s aim is o gain an unde s anding o he knowledge,
a i udes, and p ac ices (KAP) o qua an ine ho el wo ke s in China. A o al o 170 pa icipan s ook
pa in a c oss-sec ional su ey o assess he KAP o qua an ine ho el wo ke s in China, du ing he
COVID-19 pandemic. The chi-squa e es , independen - es , one-way analysis o a iance (ANOVA),
desc ip i e analysis, and bina y logis ic eg ession we e used o examine he sociodemog aphic
ac o s associa ed wi h KAP le els du ing he COVID-19 pandemic. The esul s show ha 62.41%
ha e good knowledge, 94.7% ha e a posi i e a i ude owa ds COVID-19, bu only 78.2% ha e good
p ac ices. Mos qua an ine ho el wo ke s (95.3%) a e conﬁden ha COVID-19 will be success ully
con olled and ha China is handling he COVID-19 c isis well (98.8%). Mos qua an ine ho el
wo ke s a e also aking pe sonal p ecau ions, such as a oiding c owds (80.6%) and wea ing acemasks
(97.6%). The esul s e idence ha qua an ine ho el wo ke s in China ha e acqui ed he necessa y
knowledge, posi i e a i udes and p oac i e p ac ices in esponse o he COVID-19 pandemic. The
esul s o his s udy can p o ide a e e ence o qua an ine ho el wo ke s and hei a ge ed educa ion
and in e en ion.
Keywo ds: COVID-19; qua an ine ho el wo ke s; knowledge; a i udes; p ac ices
1. Backg ound
The COVID-19 pandemic has made a signiﬁcan impac on he heal h and sa e y o
each coun y’s popula ion, as well as ongoing e ec s o hei economies and socie ies.
The Wo ld Heal h O ganiza ion has decla ed he pandemic a public heal h eme gency
o global conce n [
1
]. As posi i e cases o COVID-19 escala e, hospi als ace p oblems
wi h o e c owding and insu ﬁcien isola ion space [
2
]. Aus alia en o ces home-isola ion
o conﬁ med cases wi h mild symp oms and suspec ed cases; howe e , his ul ima ely
inc eases he isk o in ec ion o o he household membe s [
3
]. To p e en his in e ac ion,
hey p opose ha COVID-19 pa ien s wi h mild symp oms isola e hemsel es by s aying in
a ho el. In addi ion, due o inc easing conce ns ega ding ansmi ing he i us o hei
amilies, heal hca e wo ke s [4] need empo a y qua an ine accommoda ion.
To mi iga e he pandemic, coun ies a ound he wo ld ha e implemen ed sa e y
measu es such as lockdown, social dis ancing, and manda o y 14-day qua an ine pe iods
o ci izens and o eign isi o s a i ing om ab oad [
5
]. The la e esul ed in a demand
o designa ed qua an ine ho els, as his is whe e he majo i y o incoming esiden s and
isi o s will s ay. As a esul , many go e nmen s ha e exp op ia ed ho els o be used as
empo a y qua an ine accommoda ion: he ‘qua an ine ho el.’ Qua an ine ho els a e a
communi y-based public heal h in e en ion designed o mi iga e he sp ead o COVID-19
Heal hca e 2021,9, 772. h ps://doi.o g/10.3390/heal hca e9060772 h ps://www.mdpi.com/jou nal/heal hca e
105
Heal hca e 2021,9, 772
wi hin he communi y [
6
]. The use o qua an ine ho els o isola e ou is s and e u ning
esiden s o medical obse a ion o e a 14-day pe iod is he ho el indus y’s con ibu ion
o he con ol o COVID-19 [
7
]. Some schola s also a gue ha qua an ine ho els e ame he
aken- o -g an ed business model and goes beyond basic cleaning and hygiene s anda ds
o de o e g ea e a en ion o he p o ec ion and sa e y o he qua an ine gues s’ physical
and psychosocial needs, and be e ulﬁll s akeholde demands [8].
Cu en ly, in China, he COVID-19 epidemic is well-con olled; howe e , conﬁ med
cases om o e seas con inue o inc ease [
9
]. Du ing he pandemic, while hos ing qua an-
ine gues s om o e seas, qua an ine ho el wo ke s ace a much highe isk o in ec ion [
6
]
as COVID-19

s main ou e o ansmission is h ough espi a o y d ople s and di ec con ac
wi h conﬁ med cases. Addi ionally, he qua an ine ho el wo kload includes ollowing an
ope a ion guide, complying wi h high-s anda d an i-epidemic and disin ec ion measu es,
and implemen ing qua an ine se ices. The challenge o qua an ine ho el wo ke s is no
only he inc easing wo kload c ea ed by he qua an ine ho el ope a ion, bu also high
psychological s ess associa ed wi h job insecu i y, isk o exposu e, and con agion o
hemsel es, hei iends, and amilies.
Public heal h educa ion was e idenced o be he signiﬁcan measu e o mi iga e
he sp ead o he epidemic du ing he SARS, MERS, and COVID-19 pandemics [
10
,
11
].
P e ious li e a u e p oposes webina s (web-based semina s) as a public heal h educa ional
ool, and p o ide a iable me hod o ins uc ion and educa ion o school pe sonnel who
a e in e es ed in s a egies o imp o ing a school’s wellness en i onmen [
12
]. Recen ly,
some schola s ha e also e idenced ha webina s o e clea and ac ionable in o ma ion
o school s a abou disease cha ac e is ics, adop able p e en i e measu es, and ea ly
de ec ion and con ol o COVID-19 in p ima y schools [
13
]. Public heal h educa ion may
imp o e he e ec i eness o p e en i e measu es in e ms o ansmission o COVID-19
and o he i uses.
To e ec i ely cu b he COVID-19 c isis, coun ies wo ldwide a e con inuously p omo -
ing di e en unp eceden ed p e en i e measu es, including app op ia e pe sonal hygiene
and public heal h measu es [
14
]. Inco ec knowledge owa d he diseases a ec s people’s
inco ec a i ude and p ac ices di ec ly aise he isk o in ec ion. Knowledge, a i udes,
and p ac ices (KAP) is a signiﬁcan educa ional ool o public heal h and plays an in eg al
ole in de e mining a socie y’s eadiness o accep beha io al change measu es om heal h
au ho i ies [
15
]. Re e ing o he a icles, people’s KAP owa ds COVID-19 la gely a ec ed
adhe ence o con ol measu es in acco dance wi h KAP heo y [
16
–
18
]. Acco ding o he
p e ious s udies, assessing he KAP owa d COVID-19 would assis in p o iding be e
insigh o add ess poo knowledge o COVID-19. This also o e s he de elopmen o p e-
en i e s a egies and heal h p omo ion p og ams [
11
,
19
]. P e ious s udies ha e e idenced
he ela ion o a highe le el o knowledge and he p ac ice o p e en i e measu es, as
well as he posi i e ela ion o a i udes and p e en i e beha io s [
20
–
22
]. In he la es
a icles o KAP ega ding COVID-19, hey all demons a ed collec ing KAP in o ma ion
has long been use ul o in o ming p e en ion, con ol, and mi iga ion measu es du ing
he epidemic ou b eaks [23].
P io esea ch p o ides e idence ha he le el o KAP possessed by inhabi an s dic-
a es he success o he adop ed measu es [
15
,
18
,
24
–
26
]. Recen ly, he e a e some s udies in-
es iga ed KAP owa ds COVID-19 in di e en g oup, such as gene al
esiden s [19,26–36],
heal hca e wo ke s [
24
,
37
–
41
], s uden s [
9
,
42
–
48
], pa ien s [
49
], hospi al isi o s [
50
] and
slums [
51
,
52
], du ing he COVID-19 pandemic. Mos o KAP s udies ega ding COVID-19
discuss he g oup o gene al esiden s. The esul s om hese s udies ound ha esiden s
wi h a high le el o knowledge abou COVID-19 and posi i e a i udes owa d i ended
o ha e be e p e en i e beha io s and beha io al compliance [
19
,
26
]. Fu he mo e,
he e a e ewe a icles ha discuss KAP owa d he COVID-19 sys em e iew and u u e
di ec ion [53,54].
Now, he inc eased end in conﬁ med cases in China indica es hey a e coming om
o e seas. The e is an u gen need o g asp qua an ine ho el s a awa eness o COVID-19
106
Heal hca e 2021,9, 772
a his c i ical ime, as hey a e p o iding se ice o hos o e seas qua an ine gues s. To
he bes o ou knowledge, he e is no published esea ch concen a ed on he KAP o
qua an ine ho el wo ke s. The li e a u e lacks an examina ion o qua an ine ho el wo ke s’
KAP owa d COVID-19 om his pe spec i e and has a ely discussed a ge ed educa ion
and in e en ion o qua an ine ho el wo ke s in o de o comply wi h pandemic con ol
measu es. I he qua an ine ho el wo ke s’ KAPs a e conce ned abou he i us and ac o s
ha a ec hei a i ude and beha io , hen his in o ma ion can in o m ele an aining
and policies du ing hei wo k and guide hem in p io i izing p o ec ion and a oiding
occupa ional exposu e. To da e, pee - e iewed COVID-19 KAP su eys ha e comp ised
o a b ie online su ey among o dina y esiden s, heal hca e wo ke s, adul s, s uden s,
pa ien s, hospi al isi o s, and slums, and hese su eys a e no ele an in hospi ali y
indus y se ings.
To acili a e he managemen o he COVID-19 pandemic in he hospi ali y indus y,
he e is an impe a i e need o g asp he qua an ine ho el wo ke s’ awa eness o COVID-19
a his c i ical ime. This s udy aims o assess qua an ine ho el wo ke s’ KAP owa ds
COVID-19 h ough an online ques ionnai e su ey in China. The implica ion o his s udy
is o an icipa e o guide qua an ine ho elie s o de elop he key skills in he ho el indus ies
o medical educa ion, as well as an i-epidemic and disin ec ion s anda ds o hei s a
du ing and pos -pandemic.
2. Ma e ials and Me hods
2.1. S udy Design
This c oss-sec ional s udy applied con enience sampling o collec samples om he
qua an ine ho el employees in Xiamen, Fujian P o ince, China, du ing he COVID-19
pandemics, om 20 May o 10 June 2020. The e a e app oxima ely 50 qua an ine ho els in
Xiamen, as i is he only ci y in he Fujian P o ince wi h ai po s ecei ing in e na ional
ﬂigh s. The pa icipa ing s a came om se en ho els. We called he HR manage o he
qua an ine ho el and asked hem whe he hey would join he su ey. Finally, he HR
manage s o se en ho els ag eed o pos he one-page ec ui men pos e on hei WeCha
(simila o Wha sApp) employee g oup cha and in i ed employees o pa icipa e in he
su ey. The ad e isemen included a b ie in oduc ion, backg ound in o ma ion, pu pose,
p ocedu es, decla a ions o anonymi y and conﬁden iali y, and he olun a y na u e o
aking pa . The qua an ine ho el wo ke s who unde s ood he con en o he su ey and
ag eed o pa icipa e in he s udy we e ins uc ed o comple e he ques ionnai e ia clicking
on he link o scanning he QR code.
2.2. S udy Ins umen
The ques ionnai e consis ed o ou sec ions: (1) demog aphics— his su eyed pa -
icipan s’ sociodemog aphic in o ma ion, including gende , age, educa ion, and mon hly
income; (2) knowledge abou COVID-19; (3) a i ude owa d COVID-19; and (4) p ac ices
ele an o COVID-19.
To measu e COVID-19 knowledge, 12 i ems we e adap ed om Zhong e al. [
26
]. The e
we e ou i ems ega ding clinical p esen a ions (K1–K4), h ee ega ding ansmission
ou es (K5–K7), and ﬁ e ega ding p e en ion and con ol (K8–K12). ‘T ue,’ ‘ alse,’ o
‘I don’ know’ esponses we e o e ed o hese i ems. Co ec answe s sco ed ‘1

and
inco ec /unknown answe s sco ed ‘0.’ The sco e o al ange o knowledge i ems was
0–12, wi h highe sco es indica ing be e knowledge abou COVID-19. Bloom’s cu -o o
80% (≥9.6) was used o de e mine a be e knowledge [55].
A i udes we e measu ed wi h a wo-i em scale de eloped by Zhong e al. [
26
]. Pa ic-
ipan s we e asked o s a e hei le el o ag eemen on he success ul con ol o COVID-19
(1 = ag ee; 0 = No/I don’ know), and conﬁdence in winning he ba le agains he i us
(1 = yes;
0 = No). An ‘I don’ know’ esponse was conside ed as a lack o ag eemen and
hus, ‘No’ and ‘I don’ know’ we e coupled, as pe p e ious s udies [
14
,
40
]. In addi ion, he
combina ions o esponses we e conside ed o each pa icipan . The a i ude o he pa ici-
107
Heal hca e 2021,9, 772
pan s who ag eed ha COVID-19 could be success ully con olled and we e conﬁden ha
China could o e come he pandemic sco ed ‘1

and we e labeled as ‘op imis ic a i ude’ [
26
].
‘No’ o ‘I don’ know’ esponses sco ed ‘0and we e labeled ‘nega i e a i ude’ [14].
P ac ice owa d COVID-19 was measu ed wi h a wo-i em scale ha was de eloped
by Zhong e al. [
26
]. Pa icipan s we e asked o s a e hei cu en beha io s, e.g., going o
a c owded place and/o wea ing a mask when going ou (yes = 1; No = 0). Pa icipan s
who ag eed hey had no been o any c owded places and wo e a mask when lea ing hei
home sco ed ‘1

and we e labeled as ‘good p ac ice’ owa d COVID-19. The esponses ha
disag eed sco ed ‘0and we e labeled as ‘poo p ac ice’ [14].
2.3. S a is ical Analysis
The da a we e o ganized and analyzed using IBM SPSS S a is ics (S a is ical Package
o he Social Sciences) 22.0 so wa e (IBM, A monk, NY, USA). The chi-squa ed es , in-
dependen - es , and ANOVA wi h mul iple compa isons be ween each wo ca ego ies
we e done by pos hoc analysis. Leas signiﬁcan di e ence (LSD) was applied o ﬁnd
he di e ences in KAP be ween g oups o selec ed demog aphic a iables. To iden i y
ela ed ac o s, he esponse bina y logis ic eg ession analysis was applied and exp essed
as odds a io (OR) and 95% conﬁdence in e al (CI), wi h a signiﬁcance le el o 0.05 ( wo-
ailed). Fo he ﬁnal model, he Hosme –Lemeshow es [
56
], which measu es goodness
o ﬁ
(p- alue > 0.05),
was conside ed an app op ia e logis ic eg ession model. p< 0.05
was conside ed o indica e signiﬁcance in all es s. In e nal consis ency o he ques ion-
nai e’s knowledge sec ion e ealed C onbach’s alpha as 0.69, which conﬁ ms accep able
in e nal consis ency.
2.4. E hical Conside a ion
Acco ding o he ele an laws and egula ions o China and he guidelines o Yango Uni-
e si y, an e hics app o al was no equi ed o his non-in e en ional s udy
(e.g., su eys).
Ne e heless, a e qua an ine ho el manage s ag eed o pa icipa e in his s udy, and e hi-
cal app o al clea ance and in o med consen clea ance we e app o ed by he Luo, Zhong
You, Execu i e p inciple o Yango Uni e si y; hence, an e hical app o al was expec ed.
A e exp essing he p inciples o Helsinki Decla a ion, he pa icipan s we e in o med o
he pu pose o he esea ch and exp essed hei in o med consen . Pa icipan s we e made
clea ha hei pa icipa ion is olun a y. The s udy was ha mless o he pa icipan s, as no
names we e used and all da a we e analyzed anonymously in o de o main ain anonymi y.
3. Resul s
3.1. Responden Cha ac e is ics
In e ms o demog aphics among 170 pa icipan s, he e we e sligh ly mo e emale
esponden s in his s udy (n= 99, 58.2%) han he e we e male (41.8%). In e ms o
ages, 90 pa icipan s we e Millennials (53.0%) and 32 pa icipan s we e Gene a ion Z
(18.8%). In o al, 103 pa icipan s (50.6%) had a junio college and abo e deg ee. In e ms
o depa men s, 28.8% pa icipan s we e on line employees (including on desk and
housekeeping depa men s) and 71.2% pa icipan s we e logis ics suppo employees
(including ood & be e age, adminis a ion, and secu i y depa men s). One-hund ed
wen y-eigh pa icipan s (75.3%) indica ed ha hei indi idual mon hly income was 6000
RMB o below.
3.2. Assessmen o COVID-19 Knowledge
Resul s o he knowledge assessmen o qua an ine ho el wo ke s ega ding clinical
p esen a ions, ansmission ou es, and p e en ion and con ol o COVID-19 a e shown
in Table 1. The mean COVID-19 knowledge sco e o qua an ine ho el wo ke s was 9.78
(S anda d de ia ion: 1.61, ange: 0–12). The a e o o e all co ec answe o COVID-19
knowledge was 81.5% (9.78/12
×
100). The a e o o e all co ec answe o all qua an ine
ho el wo ke s anged be ween 23.5% and 98.2%. Mos wo ke s o he qua an ine ho el
108

Heal hca e 2021,9, 772
(98.2%) ecognize ha human beings who had con ac wi h conﬁ med cases should be
isola ed immedia ely o 14 days. E en so, people a e ob iously con used abou he sp ead
o i us. When asked i ea ing and con ac ing wild animals would cause in ec ion, only
23.5% answe ed co ec ly (Table 1).
Table 1. Responses o he ques ionnai e on COVID-19 KAP.
I ems Co ec Answe Ra e (n;%) Inco ec Answe and ‘I Don’
Know’ Ra e (n;%)
K1. The main clinical symp oms o COVID-19 a e e e ,
a igue, d y cough, and myalgia. 159 (93.5) 11 (6.5)
K2. Unlike he common cold, nasal conges ion, unny nose,
and sneezing a e less common among people in ec ed wi h
COVID-19 i us.
113 (66.5) 57 (33.5)
K3. A p esen , he e is no e ec i e ea men in COVID-19,
bu ea ly symp oma ic ea men can help mos pa ien s
eco e om in ec ion.
152 (89.4) 18 (10.6)
K4. No all pe sons wi h COVID-19 will de elop in o se e e
cases. Only hose who a e elde ly, ha e ch onic illnesses,
and a e obese a e mo e likely o be se e e cases.
113 (66.5) 57 (33.5)
K5. Ea ing o con ac ing wild animals would esul in he
in ec ion by he COVID-19 i us. 40 (23.5) 130 (76.5)
K6. Pe sons wi h COVID-19 canno pass he i us o o he s
when a e e is no p esen . 130 (76.5) 23.5 (4.0)
K7. The COVID-19 i us sp eads ia espi a o y d ople s
om in ec ed indi iduals. 162 (95.3) 8 (4.7)
K8. O dina y esiden s can wea gene al medical masks o
p e en in ec ion om he COVID-19 i us. 162 (95.3) 8 (4.7)
K9. I is no necessa y o child en and young adul s o ake
measu es o p e en in ec ion om he COVID-19 i us. 156 (91.8) 14 (8.2)
K10. To p e en in ec ion by COVID-19, indi iduals should
a oid going o c owded places such as ain s a ions and
a oid aking public anspo a ion.
150 (88.2) 20 (11.8)
K11. Isola ion and ea men o people who a e in ec ed
wi h he COVID-19 i us a e e ec i e ways o educe he
sp ead o he i us.
159 (93.5) 11 (6.5)
K12. People who ha e con ac wi h someone in ec ed wi h
he COVID-19 i us should be immedia ely isola ed in a
p ope place. In gene al, he obse a ion pe iod is 14 days.
167 (98.2) 3 (1.8)
A i udes Answe yes a e (n; %) Answe no a e (n;%)
A1. Do you ag ee ha COVID-19 will ﬁnally be success ully
con olled? 162 (95.3) 8 (4.7)
A2. Do you ha e conﬁdence ha China can win he ba le
agains he COVID-19 i us? 168 (98.8) 2 (1.2)
P ac ice Answe yes a e (n; %) Answe no a e (n;%)
P1. Ha e you been o any c owded places in ecen days? 33 (19.4) 137 (80.6)
P2. Do you wea a mask when you go ou in ecen days? 166 (97.6) 4 (2.4)
The independen - es and one-way ANOVA analysis we e used o assess he di -
e ences in knowledge sco es among di e en demog aphic cha ac e is ics. The esul s
showed ha he e we e no signiﬁcan di e ences in knowledge sco es o all demog aphic
a iables (gende , age, educa ion, depa men , and mon hly income) (p> 0.05, Table 2).
109
Heal hca e 2021,9, 772
Table 2.
Rela ionship be ween socio-demog aphic cha ac e is ics o he pa icipan s and hei knowledge sco es abou
COVID-19 (n= 170).
Cha ac e is ics Ca ego y Numbe o
Pa icipan s (%)
Knowledge Sco e
(Mean ±SD) /F p-Value
Gende Male a 71 (41.8) 9.54 ±1.52 −1.707 0.090
Female b 99 (51.2) 9.96 ±1.65
Age Gene a ion Z a 32 (18.8) 9.22 ±2.15
2.529 0.083
Millennials b 90 (52.9) 9.88 ±1.51
Gene a ion X c 48 (28.2) 9.98 ±1.28
Educa ion
MSB a 20 (11.8) 9.75 ±1.07
0.431 0.731
SHSVS b 47 (27.6) 9.85 ±1.43
JC c 57 (33.5) 9.91 ±1.84
UA d 46 (27.1) 9.57 ±1.70
Depa men F on line a 49 (28.8) 9.86 ±1.37 0.385 0.701
Logis ics suppo b 121 (71.2) 9.75 ±1.70
Income pe
mon h RMB #6000 and below a 128 (81.5) 9.85 ±1.53 −0.254 0.800
6001 and abo e b 29 (18.5) 9.93 ±1.46
No e: (1) Gene a ion Z = Bo n 1996+; Millennials = Bo n 1977–1995; Gene a ion X = Bo n 1965–1976. (2) MSB = Middle school and below;
SHSVS = Senio high school/ oca ional school; JC = Junio college; UA = Unde g adua e and abo e. (3)
#
Exclude ‘I don’ wan o alk
abou i ’ pa icipan s. (4) = S uden ’s es , F = analysis o a iance (ANOVA) es . (5) Mul iple compa isons be ween each wo ca ego ies
a e done by pos hoc analysis (Leas Signiﬁcan Di e ence, LSD).
Ini ially, mos (8/12) knowledge ques ions abou COVID-19 had a high accu acy
a e (80% o mo e) (Table 1). As a esul , a cu o knowledge sco e o
≤
9 was se o
poo knowledge and
≥
10 o good (adequa e) knowledge (Table 3). The s udy ound ha
62.41% o qua an ine ho el wo ke s ha e good (adequa e) knowledge, which implies ha a
signiﬁcan p opo ion o qua an ine ho el wo ke s ha e poo knowledge abou COVID-19.
Fu he , bina y logis ic eg ession analysis ound ha emale qua an ine ho el wo ke s had
highe odds o ha ing good (adequa e) knowledge a 10% signiﬁcance le el (Table 4).
Table 3. Di e ence in qua an ine ho el wo ke s’ KAP owa d COVID-19 by demog aphics (N= 170).
Cha ac e is ics
Knowledge A i ude P ac ice
Poo (n; %) Good (n;%) χ2o
(p-Value)
Nega i e (n;
%)
Op imis ic
(n;%)
χ2o
(p-Value) Poo (n;%) Good (n;
%)
χ2o
(p-Value)
O e all 64 (37.6) 106 (62.41) 9 (5.3) 161 (94.7) 37 (21.8) 133 (78.2)
Gende 5.446
(0.020) 0.278
(0.598) 0.043
(0.837)
Male 34 (47.9) 37 (52.1) 3 (4.2) 68 (95.8) 16 (22.5) 55 (77.5)
Female 30 (30.3) 69 (69.7) 6 (6.1) 93 (93.9) 21 (21.2) 78 (78.5)
Age 1.555
(0.460) 0.400
(0.819) 2.112
(0.348)
Gen Z 15 (46.9) 17 (53.1) 1 (3.1) 31 (96.9) 10 (31.2) 22 (68.8)
Millennials 31 (34.4) 59 (65.6) 5 (5.6) 85 (94.4) 18 (20.0) 72 (80.0)
Gen X 18 (37.5) 30 (62.5) 3 (6.3) 45 (93.8) 9 (18.8) 39 (81.3)
Educa ion le el 1.775
(0.620) 7.045
(0.070) 2.892
(0.409)
Middle school
and below 7 (35.0) 13 (65.0) 3 (15.0) 17 (85.0) 4 (20.0) 16 (80.0)
Senio high school/
oca ional school 19 (40.4) 28 (59.6) 4 (8.5) 43 (91.5) 8 (17.0) 39 (83.0)
Junio college 18 (31.6) 39 (68.4) 1 (1.8) 56 (98.2) 11 (19.3) 46 (80.7)
Unde g adua e
and abo e 20 (43.5) 26 (56.5) 1 (2.2) 45 (97.8) 14 (30.4) 32 (69.6)
110
Heal hca e 2021,9, 772
Table 3. Con .
Cha ac e is ics
Knowledge A i ude P ac ice
Poo (n; %) Good (n;%) χ2o
(p-Value)
Nega i e (n;
%)
Op imis ic
(n;%)
χ2o
(p-Value) Poo (n;%) Good (n;
%)
χ2o
(p-Value)
Depa men 0.024
(0.876) 0.094
(0.759) 1.873
(0.171)
F on line 18 (36.7) 31 (63.3) 3 (6.1) 46 (93.9) 14 (28.6) 35 (71.4)
Logis ics suppo 46 (38.0) 75 (62.0) 6 (5.0) 115 (95.0) 23 (19.0) 98 (81.0)
Income pe
mon h RMB #1.300
(0.254) 0.496
(0.481) 1.138
(0.286)
6000 and below 43 (33.6) 85 (66.4) 5 (3.9) 123 (96.1) 24 (18.8) 104 (81.2)
6001 and abo e 13 (44.8) 16 (55.2) 2 (6.9) 27 (93.1) 8 (27.6) 21 (72.4)
Knowledge sco e 8.25 ±1.53 10.71 ±0.68 −14.375
(0.000) 9.33 ±1.80 9.81 ±1.60 −0.860
(0.391) 9.78 ±1.57 9.78 ±1.63 0.006
(0.995)
No e: (1) Knowledge sec ion o al sco es ange om 0–12, wi h a cu o le el o
≤
9 se o poo knowledge and
≥
10 o good knowledge.
(2) The a i ude o he pa icipan s who ag eed ha COVID-19 could be success ully con olled and we e conﬁden abou China winning
agains he pandemic sco ed ‘1’ and was labeled as ‘op imis ic a i ude’ owa d COVID-19. Any o he combina ions o esponses sco ed
‘0’ and we e labeled as ‘nega i e a i ude’ owa d COVID-19. (3) The p ac ice o he pa icipan s who ag eed hey had no gone o any
c owded places and wo e a mask when lea ing home in ecen days sco ed ‘1’ and was labeled as ‘good p ac ice’ ega ding COVID-19.
Any o he combina ions o esponses sco ed ‘0’ and we e labeled as ‘poo p ac ice’ ega ding COVID-19. (4)
#
Exclude ‘I don’ wan o alk
abou i ’ pa icipan s.
Table 4.
Logis ic eg ession analysis o ac o s associa ed wi h good knowledge and op imis ic a i ude ega ding COVID-19
(N= 170).
Cha ac e is ics Knowledge A i ude
OR (95% CI) p-Value OR (95% CI) p-Value
Gende (Re e ence: Male)
Female 1.881 (0.922, 3.837) 0.082 0.522 (0.087, 3.139) 0.269
Age (Re e ence: Gene a ion Z)
Millennials 1.679 (0.605, 4.657) 0.319 9.066 (0.349, 235.311) 0.185
Gene a ion X 1.517 (0.461, 4.989) 0.493 9.656 (0.288, 323.420) 0.206
Educa ion (Re e ence: Middle school and below)
Senio high school/ oca ional school 1.292 (0.355, 4.702) 0.697 0.020 (0.001, 0.682) 0.030 *
Junio college 1.272 (0.469, 3.452) 0.636 0.151 (0.009, 2.462) 0.184
Unde g adua e and abo e 1.964 (0.797, 4.839) 0.142 1.001 (0.058, 17.420) 0.999
Depa men (Re e ence: logis ics suppo depa men )
F on line 0.723 (0.333, 1.572) 0.413 0.516 (0.079, 3.372) 0.490
Income pe mon h RMB (Re e ence: 6000 and below) #
6001 and abo e 0.460 (0.177, 1.197) 0.112 0.062 (0.003, 1.137) 0.061
Hosme –Lemeshow goodness o ﬁ s a is ic 8.277 0.309 2.050 0.979
No e: (1) #Exclude ‘I don’ wan o alk abou i ’ pa icipan s; (2) * S a is ically signiﬁcan a p< 0.05.
3.3. Assessmen o COVID-19 A i udes
To assess he a i udes owa d COVID-19, wo ques ions we e used. One asked
whe he he COVID-19 epidemic would be success ully con olled, which he majo i y o
he qua an ine ho el wo ke s ag eed wi h (95.3%). Ano he asked whe he hey us ed
China o be able o win i s ba le agains he i us, which again, he majo i y o he qua an-
ine ho el wo ke s ag eed wi h (98.8%). O e all, 94.7% o qua an ine ho el wo ke s had
an op imis ic (posi i e) a i ude owa d COVID-19, while 5.3% had a nega i e a i ude
(Table 3).
In addi ion, a i udes owa d COVID-19 we e signiﬁcan ly associa ed wi h edu-
ca ion le el (Table 3). Qua an ine ho el wo ke s who had a senio high school/ oca ional
school ( s. middle school and below, OR: 0.020, 95% CI = 0.001–0.682, p= 0.030) we e mo e
unlikely o ha e op imis ic a i ude owa d COVID-19 (Table 4).
111
Heal hca e 2021,9, 772
3.4. Assessmen o COVID-19 P ac ices
Qua an ine ho el wo ke s we e asked wo ques ions in assessmen o p ac ices ele an
o COVID-19. The ﬁ s ques ion asked whe he o no hey ag eed ha hey we e a oiding
c owded places in ecen days; he second was whe he o no hey ag eed ha hey
we e wea ing ace masks when ou side he home in ecen days. Fo he ﬁ s ques ion,
80.6% o qua an ine ho el wo ke s epo ed ha hey had been a oiding c owded places,
whe eas he emaining 19.4% had no been. Fu he mo e, 97.6% o qua an ine ho el wo ke s
epo ed wea ing a ace mask when going ou in public in ecen days, whe eas 2.4%
indica ed hey did no . In addi ion, 78.2% o qua an ine ho el wo ke s had ‘good p ac ice’
ele an o COVID-19. The emaining pa icipan s (21.8%) eco ded ‘poo p ac ice’ (Table 3).
The p ac ice ele an o COVID-19 was no signiﬁcan ly associa ed wi h all demog aphic
cha ac e is ics (Table 3).
4. Discussion
The ou b eak o COVID-19 has sen he ho el indus y in o an unp eceden ed ecession.
In his con ex , he di e en managemen policies unde aken by ho el manage s a e de e -
mining he indus y’s su i al. Qua an ine ho el wo ke s’ adhe ence o con ol measu es
is essen ial, and is la gely a ec ed by hei KAP owa ds COVID-19, in acco dance wi h
KAP heo y. The unde s anding o qua an ine ho el wo ke s’ KAP owa d he pandemic
is help ul o ho elie s when add essing and implemen ing e ec i e decision-making
amewo ks o ensu e apid esponse o unexpec ed e en s ha challenge he sol ency o
hei business. Assessing KAP ela ed o COVID-19 p o ides g ea e insigh , helping o
add ess poo knowledge abou he i us and assis wi h he de elopmen o p e en i e
s a egies and heal h p omo ion p og ams. KAP s udies p o ide baseline in o ma ion o
de e mine he ype o in e en ion ha may be equi ed o change misconcep ions abou
he i us [
14
,
15
,
24
]. To da e, he e has been limi ed published da a on qua an ine ho el
wo ke s’ KAP owa d COVID-19. The e o e, i is emendously impo an o in es iga e
he KAP o qua an ine ho el wo ke s o help guide hese e o s.
In China, he o e all COVID-19 ‘co ec ’ knowledge a e among qua an ine ho el
wo ke s is 81.5%, wi h an a e age sco e o mode a e (9.78
±
1.61). This knowledge sco e is
highe han ha o US esiden s (80%) [
34
] and he Pales inian popula ion (79%) [
57
], bu
lowe han he Chinese gene al popula ion (90%) [
26
] and Tanzanian esiden s (84.4%) [
11
].
This s udy ound ha 62.41% o qua an ine ho el wo ke s in China ha e good (adequa e)
knowledge o COVID-19, which means he e is a conside able p opo ion o qua an ine
ho el wo ke s who ha e poo knowledge. Recen ly, he esea ch esul s p o ide e idence
ha he le el o knowledge ega ding COVID-19 was p opo ional o age and yea s o edu-
ca ion [
58
]. Howe e , his empi ical esul e eals ha he e we e no signiﬁcan di e ences
in knowledge owa d COVID-19 sco es o he demog aphic a iables (age, educa ion, de-
pa men , and mon hly income). Tha esul is no consis en wi h o he s udies conduc ed
wo ldwide, which shows knowledge was signiﬁcan ly di e ed ac oss age, educa ion le el,
and income [
26
,
27
]. Ou s udy demons a ed he emale qua an ine ho el wo ke s we e
mo e likely o ha e good (adequa e) knowledge compa ed o men, which is consis en wi h
he con en ions o Zhong e al. [
26
] and Banik e al. [
28
], and is simila o a c oss-cul u al
KAP s udy by Ali e al. [
59
]. This esul may be explained by gende di e ence in ela ed
ac i i ies, and can also be a ibu ed o he ac ha women will expe ience highe amily
p essu e in hei ole o ca ing o amilies.
As a conside able amoun o qua an ine ho el wo ke s in China ha e poo knowledge
o COVID-19, qua an ine ho elie s should p o ide ex a medical educa ion o iden i y
mic obiological cha ac e is ics and pe o m diagnosis, disin ec ion, and sel -p o ec ion
echnology. Recen ly, some a icles ha e ad oca ed ha ho elie s should imp o e he
se ice o hygiene and cleaning, disin ec ion, and hygiene ac i i ies as he main con en s
esponse o he ho el indus ies de elopmen o pos -COVID 19 [
60
–
62
]. Following he
schola s, app op ia e aining in ope a ion guides, complying wi h an i-epidemic and
disin ec ion s anda ds, and implemen ing qua an ine se ices is also essen ial.
112
Heal hca e 2021,9, 755
In his pape , we a emp o measu e he ela i e e ﬁciency in p e en ing he sp ead
o COVID-19 using he da a en elopmen analysis (DEA) echnique. In p ac ice, he DEA
echnique has been widely used in a ious applica ions, including heal h indus ies [
5
,
6
],
ene gy sec o s [
7
–
9
], cemen indus ies [
10
], ag icul u al p oduc ion [
11
,
12
], and manu ac-
u ing sec o s [
13
], and i has p o en o be an e ec i e app oach in iden i ying he bes
p ac ice on ie s.
In he ﬁeld o medical se ices, DEA was also widely used o measu e he e ﬁciency
o hospi als in associa ion wi h pa ien isi s, su ge ies, and discha ges. Fo example,
Khushalani and Ozcan [
14
] employed a dynamic ne wo k DEA o examine he e ﬁciency
o p oduc ion quali y in hospi als and ound ha u ban and eaching hospi als we e less
likely o imp o e quali y p oduc ion e ﬁciency. Deily and McKay [
15
] used e ﬁciency sco es
ob ained om a DEA analysis as explana o y a iables o de e mine hospi al e ﬁciency.
In o he ﬁelds, Oggioni e al. [
10
] employed DEA o analyze e ﬁciency by using ene gy
as an inpu and one desi ed ou pu accompanied by undesi ed ou pu s (CO
2
emissions).
Mousa i-A al e al. [
11
] and Mohammadi e al. [
12
] applied he DEA echnique o measu e
he e ﬁciency o ag icul u al p oduc ion o iden i y was e ul ene gy. Vazhayil and Balasub-
amanian [
9
] showed ha he weigh - es ic ed s ochas ic DEA me hod was app op ia e o
op imize powe sec o s a egies.
To compa e he mi iga ion e ﬁciency among coun ies on a ai basis, he ime pe iod
o each s age was calcula ed om he da e o he ﬁ s conﬁ med case in each coun y. The
whole pe iod co e s 105 days om he ﬁ s conﬁ med case and was di ided in o six s ages.
In addi ion o he measu emen o o e all e ﬁciency co e ing 105 days, he e ﬁciency a
each s age was also e alua ed. Fi s ly, he pu pose o his a icle was o compa e he ela i e
e ﬁciency o each coun y in mi iga ing he sp ead o he COVID-19 epidemic. Secondly,
he ends o e ﬁciency ank ac oss s ages o each coun y we e analyzed. E en ually, an
indica o o epidemic s abili y was de eloped o judge he s a us o epidemic s abili y o
each coun y.
2. Resea ch Me hods
To compa e he ela i e e ﬁciency in p e en ing and educing he sp ead o COVID-19,
a o al o 23 coun ies we e selec ed, including 19 coun ies in he G20 and ou o he
ep esen a i e coun ies, as lis ed in Table 1. The eason o he selec ion o I an and
Spain was due o hei high le els o conﬁ med cases and dea hs. Pakis an and Nige ia
we e chosen due o hei la ge popula ions, which eached 220.9 million and 206.1 million,
espec i ely, a he end o 2020 [16].
Table 1. The s a ing and ending da es o each s age o each coun y.
Coun y S age 1 S age 2 S age 3 S age 4 S age 5 S age 6
China 2019/12/31–2020/1/30 2020/1/31–02/14 02/15–02/29 02/30–03/15 03/16–03/30 03/31–04/14
Japan 01/15–02/14 02/15–02/29 03/01–03/15 03/16–03/30 03/31–04/14 04/15–04/29
Ko ea 01/20–02/19 02/20–03/05 03/06–03/20 03/21–04/04 04/05–04/19 04/20–05/04
USA 01/23–02/22 02/23–03/08 03/09–03/23 03/24–04/07 04/08–04/22 04/23–05/07
Aus alia, F ance 01/25–02/24 02/25–03/10 03/11–03/25 03/26–04/09 04/10–04/24 04/25–05/09
Canada 01/27–02/26 02/27–03/12 03/13–03/27 03/28–04/11 04/12–04/26 04/27–05/11
Ge many 01/28–02/27 02/28–03/13 03/14–03/28 03/29–04/12 04/13–04/27 04/28–05/12
India 01/30–02/29 03/01–03/15 03/16–03/30 03/31–04/14 04/15–04/29 04/30–05/14
I aly 01/31–03/01 03/02–03/16 03/17–03/31 04/01–04/15 04/16–04/30 05/01–05/15
Russia, Spain, UK 02/01–03/02 03/03–03/17 03/18–04/01 04/02–04/16 04/17–05/01 05/02–05/16
I an 02/20–03/21 03/22–04/05 04/06–04/20 04/21–05/05 05/06–05/20 05/21–06/04
B azil, Pakis an 02/27–03/28 03/29–04/12 04/13–04/27 04/28–05/12 05/13–05/27 05/28–06/11
Nige ia 02/28–03/29 03/30–04/13 04/14–04/28 04/29–05/13 05/14–05/28 05/29–06/12
Mexico 02/29–03/30 03/31–04/14 04/15–04/29 04/30–05/14 05/15–05/29 05/30–06/13
Indonesia 03/02–04/01 04/02/04/16 04/17–05/01 05/02–05/16 05/17–05/31 06/01–06/15
Saudi A abia 03/03–04/02 04/03–04/17 04/18–05/02 05/03–05/17 05/18–06/01 06/02–06/16
A gen ina 03/04–04/03 04/04–04/18 04/19–05/03 05/04–05/18 05/19–06/02 06/03–06/17
Sou h A ica 03/06–04/05 04/06–04/20 04/21–05/05 05/06–05/20 05/21–06/04 06/05–06/19
Tu key 03/12–04/11 04/12–04/26 04/27–05/11 05/12–05/26 05/27–06/10 06/11–06/25
The WHO [
1
] di ided he s ages o ansmission in o (1) no cases epo ed o obse ed
(S age 0); (2) impo ed cases (S age 1); (3) localized communi y ansmission (S age 2); and
(4) la ge-scale communi y ansmission (S age 3). As he da e o he ﬁ s conﬁ med case
119

Heal hca e 2021,9, 755
a ied ac oss coun ies, he pe iod o each s age was no based on he same da e among
hese coun ies bu was calcula ed ins ead om he da e o he ﬁ s conﬁ med case in each
coun y. The da e o he ﬁ s conﬁ med case was iden iﬁed based on he daily si ua ion
epo eleased by he WHO [
1
] s a ing on 21 Janua y 2020. Among he 23 coun ies
selec ed, China, Japan, and Ko ea epo ed ha ing conﬁ med cases o COVID-19 be o e
21 Janua y 2020. The in o ma ion eleased om he WHO [
1
] demons a ed ha some
cases o pneumonia o unknown e iology we e de ec ed in Wuhan Ci y, Hubei P o ince,
China, on 31 Decembe 2019. On 7 Janua y 2020, a new ype o co ona i us was isola ed
and iden iﬁed. Thus, he ﬁ s case in China may be conside ed o ha e occu ed a he end
o 2019. Acco ding o he WHO [
1
], he ﬁ s conﬁ med cases o COVID-19 in Japan and
Ko ea we e epo ed on 15 and 20 Janua y 2020, espec i ely.
The o e all e ﬁciency was compa ed based on he whole pe iod co e ing 105 days
since he ﬁ s conﬁ med case o each coun y. The de elopmen p ocess o COVID-19
sp ead was sepa a ed in o 6 s ages. As he numbe o new conﬁ med cases epo ed in
ea lie days is much lowe , S age 1 co e s he ﬁ s 30 days a e he ﬁ s conﬁ med case in
each coun y. Each s age om S age 2 o S age 6 co e ed 15 days. The s a ing and ending
da es o each s age o each coun y a e lis ed in Table 1.
2.1. The DEA Model
In his pape , he DEA model was employed o measu e he mi iga ion e ﬁciency
ega ding he sp ead o COVID-19 a each s age o each coun y. The DEA model, p oposed
by Cha nes e al. [
17
] based on he on ie p oduc ion unc ion deﬁned by Fa ell [
18
], is
a nonpa ame ic echnique o measu ing he ela i e e ﬁciency o each decision-making
uni (DMU) [
19
]. The mi iga ion o COVID-19 ansmission in each coun y was execu ed
by a echnology whe eby Ncoun ies in e ms o DMUs ans o m a non-nega i e ec o
o mul iple inpu s, deno ed
x=
(
x1
,
...
,
xm
)
∈m
+
, in o a non-nega i e ec o o mul iple
ou pu s, deno e
y=
(
y1
,
...
,
ys
)
∈s
+
. This pape employed he basic DEA model o
Cha nes, Coope s, and Rhodes (CCR) o calcula e he e ﬁciency o COVID-19 ansmission
mi iga ion. The CCR model, unde he hypo hesis o cons an e u ns o scale, is exp essed
as ollows:
Min θ
s. .θx0−Xλ≥0
Yλ≥y0
λ≥0
(1)
whe e
y0
is he ou pu ,
x0
is he inpu ,
Xand Y
a e he da ase s in he ma ices,
λ
is a
semiposi i e ec o , and θ ep esen s he echnical e ﬁciency.
A e he e ﬁciency a each s age was ob ained, Pea son co ela ion es s we e con-
duc ed be ween he di e en s ages a a p- alue < 0.01 o examine he a ia ion in e ﬁciency
anks ac oss s ages. The co ela ion es s we e used o explain he impac o he e ﬁciency
anks a p e ious s ages on subsequen s ages.
In his pape , epidemic s abili y (ES) is deﬁned as he eco e y s a us om he epi-
demic, and he indica o ES is p esen ed by measu ing he a e age inc ease in he p opo -
ion o conﬁ med cases o popula ion (PCCP) du ing he pe iod o he las day o S age 6
and a day designa ed o es a he economy, exp essed as ollows:
ES =S −S0
Δ (2)
whe e
S
and
S0
deno e he PCCP on he las day o S age 6 and he designa ed day,
espec i ely, and Δ ep esen s he pe iod be ween he wo da es.
2.2. The Va iables
E ﬁciency, desc ibed as he ela i e pe o mance ega ding he educ ion in COVID-19
ansmission, was measu ed in his pape using he DEA me hod and is s a ed in he o m
120
Heal hca e 2021,9, 755
o an ou pu /inpu a io. The objec i e o he au ho i y adminis a ion was o minimize he
o al conﬁ med cases ha occu ed in each s age wi h a gi en amoun o esou ces used.
Coope e al. [
19
] sugges ed ha he DEA echnique can be easily applied o a mul iple
inpu –ou pu amewo k o compa e he ela i e e ﬁciency among a ious DMUs. The
in o ma ion p oduced om he DEA is aluable o iden i ying speciﬁc e ﬁcien uni s o
u u e lea ning [20].
Neide ud [
21
] sugges ed ha he ise o megaci ies may yield po en ial isks o new
epidemics and become a h ea in he wo ld. The high human popula ion densi y and close
human- o-human con ac a e majo sou ces o he apid sp ead o espi a o y diseases o
a ian ﬂu. The g ow h and densi y o he human popula ion may wo k as an incuba o o
in ec ious diseases, and u baniza ion as a d i e o disease may ha e a nega i e e ec on
public heal h [
22
,
23
]. Thus, a iables including (1) newly conﬁ med cases n, (2) popula ion
densi y d, and (3) u baniza ion deg ee u o each coun y we e employed o measu e he
ela i e e ﬁciency. As mo e conﬁ med cases ep esen less e ﬁciency, newly conﬁ med
cases nwas ea ed as an inpu a iable in Equa ion (1) o measu e mi iga ion e ﬁciency. In
essence, he highe he popula ion densi y and u baniza ion o a coun y a e, he g ea e
he chance o in ec ion is. Thus, popula ion densi y dand u baniza ion deg ee uwe e
ea ed as ou pu a iables in Equa ion (1) o he measu emen o mi iga ion e ﬁciency.
2.3. Da a Collec ion
The da a o accumula ed conﬁ med cases we e ex ac ed om he daily si ua ion
epo s om he WHO [
1
], and he o al conﬁ med cases in each s age we e calcula ed by he
di e ence in he accumula ed conﬁ med cases on he las day o each s age and he p e ious
s age. The popula ion densi y da a o each coun y we e p o ided by Wo ldome e [
24
],
and he u baniza ion deg ee da a we e ex ac ed om he Wo ld Bank [
16
]. The desc ip i e
s a is ics o he o al accumula ed conﬁ med cases ac oss he 6 s ages (i.e., 105 days since
he ﬁ s conﬁ med case), popula ion densi y and u baniza ion deg ee a e p esen ed in
Table 2. By he end o S age 6 (i.e., 105 days since he ﬁ s conﬁ med case), he USA
had 1,193,452 conﬁ med cases, anking a he op o he 23 coun ies, while Aus alia
had he lowes numbe (6914) o conﬁ med cases. Ko ea had he highes popula ion
densi y a 527.30 pe sons pe km
2
, while Aus alia had a much lowe popula ion densi y a
3.32 pe sons pe km
2
. A gen ina had he la ges u baniza ion deg ee a 92% and anked a
he op. In con as , he u baniza ion deg ee o India was much lowe han he a e age o
71.48% based on he o he coun ies and was only 34%.
Table 2. Desc ip i e s a is ics o s udy a iables.
S a is ics To al Conﬁ med
Cases n
Popula ion Densi y
d(Pe son Pe km2)
U baniza ion Deg ee
u(%)
Max. 1,193,452 527.30 92.00
Min. 6914 3.32 34.00
A e age 190,093 151.40 71.48
S anda d de ia ion 260,495 146.28 15.45
The e ﬁciency sco e was calcula ed h ough he assis ance o he so wa e DEA
sol e 13.
3. Resul s
The e ﬁciency o COVID-19 mi iga ion co e ing he ﬁ s 105 days a e a conﬁ med
case o each o he coun ies is depic ed in Figu e 1. Aus alia and Ko ea ank a he op in
e ms o mi iga ion e ﬁciency. In con as , he USA anks a he bo om, ollowed by B azil
and Russia. The majo cause a ec ing he e ﬁciency ank may be a ibu ed o he numbe
o o al conﬁ med cases occu ing o e he whole pe iod. The o al conﬁ med cases in
Aus alia and Ko ea in he whole pe iod (co e ing 105 days since he ﬁ s conﬁ med case)
121
Heal hca e 2021,9, 755
we e only 6667 cases and 10,801 cases, espec i ely, while he USA, B azil, and Russia had
1,193,452; 739,503, and 272,043 cases, espec i ely.
Figu e 1. Mi iga ion e ﬁciency sco es among he 23 coun ies.
The e ﬁciency sco es and anks a each s age o each coun y we e also calcula ed
acco ding o Equa ion (1). Based on he shape o he e ﬁciency anking end, hese
coun ies we e classiﬁed in o ﬁ e ypes, as depic ed in Figu e 2.
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Figu e 2. The ends in e ﬁciency ank o coun ies o Types (1)–(5).
122
Heal hca e 2021,9, 755
3.1. Type (1): An In e ed U-Shaped Pa e n Including Ko ea, China, I aly, Spain, UK, Ge many,
and F ance
This pa e n in he e ﬁciency ank ends was cha ac e ized by a con inual decline
in mi iga ion e ﬁciency om S age 1, which, a e eaching he lowes poin in he e ﬁ-
ciency anks, con inued o imp o e un il he las s age (S age 6). E o s o mi iga e newly
conﬁ med cases h ough he implemen a ion o esponse s a egies may ha e e en ually
achie ed a ce ain e ec . In essence, he mi iga ion e ﬁciency in Type (1) g adually de e i-
o a ed in he middle s ages. Passing h ough he peak o daily new conﬁ med cases, he
COVID-19 ansmission was hen educed, and he e ﬁciency s a ed o imp o e h ough
he las s age. Fo example, I aly anked 14 h in S age 1 and hen d opped o 20 h in
S age 2. I aly hen eached a peak o daily conﬁ med cases, amoun ing o 6557 cases on
22 Ma ch 2020, which occu ed in S age 3. A e S age 3, he COVID-19 ansmission in
I aly imp o ed, and he e ﬁciency ank ose o 13 h place in S age 6. The e ﬁciency anks
o China a e S age 3 and o Ko ea a e S age 2 showed g ea imp o emen and a ained
a ela i ely mo e s able s a e. China anked 21s place and 22nd place a S age 1 and S age
2, espec i ely, bu he e ﬁciency ank was imp o ed o 2nd place a S age 4 and 3 d place
a S ages 5 and 6 h ough a g ea numbe o eme gency esponse s a egies. Simila o
China, Ko ea anked in 10 h place and 13 h place o mi iga ion e ﬁciency a S ages 1 and
2, espec i ely, and he e ﬁciency imp o ed o 6 h place a S age 3 and ﬁ s place a S age
4, which was subsequen ly main ained un il he ﬁnal s age. The o he coun ies showed
simila p ocesses, bu he deg ee o e ﬁciency imp o emen was di e en .
3.2. Type (2): An In e ed N-Shaped Pa e n Including Japan and Aus alia
In his ype, he e ﬁciency ank ﬂuc ua ed ac oss s ages, wi h ini ial imp o emen s
ollowed by de e io a ion in he middle s ages, bu e en ually, he e ﬁciency ank imp o ed
in he ﬁnal s ages. Fo example, he e ﬁciency ank o Japan imp o ed con inuously om
12 h place in S age 1 o 6 h place in S age 2 o ﬁ s place in S age 3, hen d opped o 4 h
place in S age 4 and 6 h place in S age 5, and e en ually imp o ed o 4 h place again.
3.3. Type (3): Con inual Dec eases in E ﬁciency Rank Including Russia and India
The end pa e n in e ﬁciency ank o Type (3) coun ies is cha ac e ized by he
g adual de e io a ion in mi iga ion e ﬁciency. The e ﬁciency anks a e no bad in he ea lie
s ages, bu hey wo sen p og essi ely. Fo example, Russia pe o med a he highes le el
ega ding mi iga ion e ﬁciency in S age 1 and was anked in ﬁ s place. Un o una ely,
Russia did no main ain his ad an age, and i s ank con inued o de e io a e o 4 h place
in S age 2 and, ﬁnally, o 21s place in S age 6.
3.4. Type (4): U-Shaped Pa e n Including he USA, I an, Tu key, Indonesia, Pakis an, Sou h
A ica, A gen ina, and B azil
This end in he e ﬁciency anks is cha ac e ized by some imp o emen s in mi iga ion
e ﬁciency in he middle s ages ha e en ually ebound back o a wo se s a e. Fo example,
he esponse in he USA o a oid COVID-19 ansmission was no bad in S ages 1 and 2,
as i anked in 8 h place and 5 h place, espec i ely. Howe e , i s e ﬁciency con inually
and d ama ically d opped a e S age 2 and ell o 23 d place ( he bo om o he anking)
in S ages 5 and 6. The e ﬁciency imp o emen om S age 1 o S age 2 in he USA may be
a ibu ed o i s p omp a el es ic ions on China om 2 Feb ua y 2020 and addi ional
a el es ic ions on I an, I aly, and Ko ea on 29 Feb ua y [
25
]. The g adual de e io a ion
in e ﬁciency anking in he la e s ages in he USA implies ha i s esponse s a egies may
be ine ec i e o a oiding he epidemic.
The end pa e n in he e ﬁciency anking o B azil p o ides a di e en s o y. F om
S age 1 o S age 6, he e ﬁciency anks o B azil we e no good. On 25 June 2020 ( he ﬁnal
obse a ion poin in S age 6) in B azil, newly conﬁ med cases emained a a high le el,
amoun ing o 39,436 cases. This implies ha he esponse s a egies adop ed by B azil
con ained ﬂaws.
123
Heal hca e 2021,9, 755
3.5. Type (5): N-Shaped and W-Shaped Pa e ns Including Mexico, Nige ia, and Saudi A abia
An N-shaped pa e n o Mexico and W-shaped pa e ns o Nige ia and Saudi A abia
we e iden iﬁed. A he middle s ages, he e ﬁciency anks o hese Type (5) coun ies
ﬂuc ua ed e y much. Fo example, Mexico anked 13 h place a S age 1 and hen d opped
and ose in he middle s ages, e en ually d opping again o 17 h place a S age 6. As he e -
ﬁciency o hese wo pa e ns d ops again in he las s ages, his implies ha he mi iga ion
e ﬁciency is no s able and ha he u u e ends o hese coun ies a e no op imis ic.
To examine he impac o he e ﬁciency ank a he p e ious s age on he subsequen
s age, a Pea son co ela ion es o e ﬁciency sco es be ween di e en s ages was conduc ed.
The esul s a e lis ed in Table 3. The co ela ion coe ﬁcien be ween S age 1 and S ages 4–6
was e y low, anging om 0 o
−
0.1433. In con as , he co ela ion coe ﬁcien was 0.788
be ween S age 4 and S age 5, 0.760 be ween S age 4 and S age 6, and 0.983 be ween S age 5
and S age 6. Table 3 also shows ha he g ea e he dis ance is be ween any wo s ages, he
lowe he co ela ion coe ﬁcien is.
Table 3. Co ela ions o mi iga ion e ﬁciency be ween di e en s ages.
S age 1 S age 2 S age 3 S age 4 S age 5 S age 6
S age 1 1
S age 2 0.6739 *** 1
S age 3 0.4048 ** 0.5666 *** 1
S age 4 −0.1433 0.0210 0.4297 ** 1
S age 5 −0.0982 0.1918 0.2002 0.7884 *** 1
S age 6 −0.0824 0.1401 0.1783 0.7602 *** 0.9828 *** 1
**: p≤0.05; ***: p≤0.01.
A nume ical example is p esen ed in his pape , in which i was p oposed ha he
a el es ic ions we e li ed on he designed da e o 27 June 2020; ES,
S
,
S0
, and
Δ
we e
calcula ed acco ding o Equa ion (2) o hese 23 coun ies, and he esul s a e lis ed in
Table 4, whe e
S
and
S0
a e measu ed by cases pe 100,000 pe sons,
Δ
in days, and ES by
cases pe 1,000,000 pe sons. The anking o each coun y lis ed in Table 4 is based on he
alue o epidemic s abili y (ES).
Table 4 indica es ha India has he lowes alue o
S0
(PCCP in 105 days), amoun ing
o 5.65 cases pe 100,000 pe sons, a sligh ly lowe alue han ha o China (5.81 cases
pe 100,000 pe sons). In con as , Spain and Saudi A abia ha e he highes alues o
S0
,
amoun ing o 492.32 and 379.30 cases pe 100,000 pe sons, espec i ely, which a e much
highe han he a e age o 172.19 cases pe 100,000 pe sons. Howe e , he anking o he
PCCP on 27 June 2020 (
S
) changes e y much. China anks a he op wi h he lowes
S
,
amoun ing o 5.92 cases pe 100,000 pe sons. The PCCP in India inc eases e y much om
5.65 a
S0
o 36.88 cases pe million a
S
. The USA has he highes alue a
S
, amoun ing
o 727.37 cases pe 100,000 pe sons.
Table 4 also demons a es ha he ES in China, Japan, Ko ea, and Aus alia is much
be e han ha in he o he coun ies, amoun ing o 0.01, 0.46, 0.68, and 0.89 cases pe
million pe sons pe day, espec i ely, du ing he pe iod be ween he las day o S age 6 and
27 June 2020. In con as , he ES in B azil, Saudi A abia, Sou h A ica, and he USA eaches
143.67, 93.97, 85.78, and 71.92 cases pe million pe sons pe day, espec i ely. Based on he
alues o ES, i is sugges ed ha he u u e ends ega ding he pandemic in B azil, Saudi
A abia, Sou h A ica, and he USA a e no op imis ic and a e ull o challenges.
124

Heal hca e 2021,9, 755
Table 4. The epidemic s abili y o each coun y by ank.
DMU S0S Δ ES Rank
China 5.81 5.92 74 0.01 1
Japan 12.04 14.47 59 0.46 2
Ko ea 21.07 24.68 54 0.68 3
Aus alia 27.11 29.78 30 0.89 4
Nige ia 7.06 11.3 15 2.83 5
Indonesia 13.99 18.74 12 3.95 6
Ge many 203.51 230.64 46 5.90 7
I aly 368.99 396.88 43 6.49 8
India 5.65 36.88 44 7.10 9
Spain 492.32 530.22 42 9.02 10
F ance 209.24 239.23 30 10.00 11
Tu key 227.25 230.63 2 16.92 12
Canada 180.16 271.9 47 19.52 13
Pakis an 54.12 90.04 16 22.45 14
UK 348.69 455.71 42 25.48 15
I an 191.32 259.22 21 32.33 16
Mexico 103.91 157.41 14 38.21 17
A gen ina 72.54 116.07 10 43.53 18
Russia 186.41 430.09 42 58.02 19
USA 360.56 727.36 51 71.92 20
Sou h A ica 141.45 210.07 8 85.78 21
Saudi A abia 379.3 501.46 13 93.97 22
B azil 347.9 577.77 16 143.67 23
S0
: epidemic s abili y on he designa ed da e (27 June 2020);
S
: he las day o S age 6;
Δ
: he pe iod be ween he
designa ed da e and he las day o S age 6; ES: epidemic s abili y.
4. Discussion
The DEA in his pape shows ha Ko ea, Aus alia, and Japan had be e mi iga ion
e ﬁciency by 27 June 2020, while he USA, B azil, and Russia pe o med less e ﬁcien ly
and we e anked a he bo om. Ahn [
26
] sugges ed ha he success ul expe ience in
Ko ea o coun e COVID-19 sp ead may be a ibu ed o he mass es ing and e ec i e
con ac acking sys em. Indi iduals es ing posi i e o he in ec ion a e i al es s we e
hospi alized a special acili ies. The people who had been in con ac wi h he in ec ed we e
o emain sel -qua an ined o 14 days. The a ailabili y o pe sonal p o ec i e equipmen
was ensu ed o ha e a su ﬁcien supply o a oid u he in ec ion a he onse o COVID-19
in Ko ea. In con as , he es ing capaci y has no been su ﬁcien o suppo he policies o a
g adual eopening o he economy planned in many US s a es [27].
4.1. The T end Pa e ns in E ﬁciency Ranks
The end pa e ns in e ﬁciency anks also e ealed in o ma ion abou u u e ends
ega ding epidemic mi iga ion. Type (1) and Type (2) coun ies may ha e mo e op imis ic
chances ega ding eco e y om he sp ead o COVID-19, as he e ﬁciency anks o Type (1)
and Type (2) coun ies we e high in S age 6.
The Type (1) coun ies included he ollowing se en coun ies: Ko ea, China, I aly,
Spain, he UK, Ge many, and F ance.
In addi ion o Ko ea, he o he coun ies implemen ed e ec i e esponsi e s a egies,
including ex ensi e i al es s, lockdowns, social dis ancing, empo a y cessa ion o spo s
e en s, school closu es, and wea ing o masks. In China, es ing policies we e p omo ed by
expanding he es ing o indi iduals om pe sons wi h symp oms o he open public on
12 Feb ua y 2020, and all le els o school we e closed on 26 Janua y 2020 [
28
,
29
]. China has
success ully slowed he ansmission o COVID-19 h ough a combina ion o lockdowns,
i al es s, con ac ing acing, and o he mino s a egies, including s ee sani iza ion,
school closu es, and wea ing o masks. S ic lockdowns and s ic checks o a oid close
con ac be ween people we e implemen ed in China a e he ou b eak. In less han h ee
mon hs, China g adually eased he s ic policy o he lockdown and s a ed o mo i a e
125
Heal hca e 2021,9, 755
he opening o economic ac i i ies. The s ic lockdowns, wea ing o masks, and social
dis ancing implemen ed in China may be he majo con ibu o s o he e ec i e p e en ion
o ansmission in a sho ime.
In con as , he esponse o Eu opean coun ies such as I aly was no as p omp and
u gen as ha in Ko ea o China, and hei e ﬁciency anks a e S age 4 we e wo se. Fo
example, schools in I aly closed on 2 Ma ch 2020, and people we e asked o s ay a home,
wi h excep ions o daily exe cise and g oce y shopping, on 23 Feb ua y 2020. Howe e ,
he es ing policy adop ed in I aly ocused on es ing anyone wi h COVID-19 symp oms
a e 26 Feb ua y [
28
,
29
]. Howe e , he e ﬁciency anks o he UK in he la e s ages
(S ages 4–6) we e much wo se han hose o o he Eu opean coun ies. In Ma ch 2020, he
UK a emp ed o educe he impac o COVID-19 by means o he d immuni y, bu la e , i
denied he claims o he d immuni y and a gued ha he d immuni y is a na u al by-p oduc
o an epidemic [
30
]. Gi en his si ua ion, he s a egy o ﬁgh agains he epidemic was
delayed, and hus, he e ec was educed.
Type (2) coun ies consis ed o only Japan and Aus alia, wi h o e all e ﬁciency anks
o ﬁ s and hi d place, espec i ely. In he middle s ages, he e ﬁciency anks ini ially
imp o ed and hen g ew wo se. A possible cause o hese changes in e ﬁciency anks may
be he low le els o i al es ing in he ea lie s ages.
Ex ensi e i al es s we e pe o med in Aus alia and amoun ed o nea ly 1000 es s
pe 100,000 people in he popula ion by 31 Ma ch 2020 [
31
]. This numbe con inued o
inc ease and eached 2081 es s pe 100,000 people on 28 Ap il 2020 and 3119 es s pe
100,000 people on 9 May 2020 ( he ﬁnal obse a ion poin in S age 6 o Aus alia). The
high es ing a e in Aus alia may ha e been a majo ac o in mi iga ing he inc ease in
new cases and leading i o ha e he bes o e all e ﬁciency among hese 23 coun ies.
In con as , he end in e ﬁciency anks o Type (3) coun ies showed a con inual
de e io a ion in mi iga ion e ﬁciency. Compa ed o o he coun ies, he co ona i us es ing
a e pe capi a in India was e y low, eaching a o al o 144,910 es s in a popula ion wi h
mo e han 1.3 billion people by 9 Ap il 2020 [
32
]. On 14 May 2020 ( he ﬁnal obse a ion
poin in S age 6 o India), he i al es ing a e was only 1.41 es s pe 1000 people [
29
].
The low es ing a e may be a key ac o in explaining he good pe o mance based on he
high-e ﬁciency anking om S age 1 o S age 4. Wi hou es ing, no da a a e gene a ed; hus,
highe e ﬁciency sco es a e ob ained. As o 27 June 2020, he o al numbe o conﬁ med
cases in India eached 508,953, which was abou 6.5 imes he o al numbe o conﬁ med
cases o 78,003 du ing he en i e pe iod as o 14 May 2020.
A he onse o he ou b eak, Russia announced a empo a y ban on Chinese ci izens
om en e ing Russia on 20 Feb ua y 2020 [
25
]. This s a egy may ha e been e ec i e in
p e en ing in ec ion h ough impo ed cases om China in S age 1 and S age 2. Ex ensi e
es ing had been conduc ed in Russia, including 0.32 es s pe 1000 people on 5 Ma ch 2020,
1.12 es s pe 1000 people on 22 Ma ch 2020, 4.38 es s pe 1000 people on 4 Ap il 2020,
11.06 es s pe 1000 people on 16 Ap il 2020, 27.04 es s pe 1000 people on 2 May 2020, and
45.61 es s pe 1000 people on 16 May 2020 ( he las day o S age 6). Howe e , Russia’s
heal h depa men admi ed ha he es ki s we e o en w ong and p o ided alse-nega i e
esul s. The e o e, he es ed people wi h he i us we e allowed o go home and hus
in ec ed o he people. Thus, he eal numbe o in ec ed indi iduals was mo e han iple
he o ﬁcial ﬁgu e [
33
]. The ine ec i e es s may explain he con inual de e io a ion in
e ﬁciency sco es o Russia.
Type (4) coun ies con ained he ollowing nine coun ies: he USA, I an, Tu key,
Canada, Indonesia, Pakis an, Sou h A ica, A gen ina, and B azil. I he cu en ends o
hese coun ies con inue in o he u u e, he ou comes do no look op imis ic ega ding
he epidemic, and hese coun ies need o de o e mo e e o o imp o ing mi iga ion in
newly conﬁ med cases as hei e ﬁciency anks we e poo in he ﬁnal s ages. Some Type
(4) coun ies lacked es ing capaci y in he ea lie s ages o he pandemic, and hus, he
amoun o es ing ha was pe o med was much lowe han needed. Due o ha ing less
i al es ing han he ac ual need, unde es ima ion o newly conﬁ med cases may ha e
126
Heal hca e 2021,9, 755
aken place and led o he illusion o e ﬁciency imp o emen , bu e en ually, e ﬁciency
anks d opped in he ﬁnal s ages.
In he USA, he o al numbe o es s pe o med ela i e o he size o he popula ion
be o e 7 Ma ch 2020 was e y low, a less han 0.01 es s pe 1000 people, and he si ua ion
g adually imp o ed in Ma ch 2020 (in S age 3). The es ing a e inc eased o 0.23 es s pe
1000 people by he end o Ma ch 2020 (in S age 4) and hen quickly inc eased o 10.43 es s
pe 1000 people on 16 Ap il 2020 (in S age 5). On he day o he ﬁnal obse a ion poin
in S age 6 (7 May 2020), he es ing a e ose o 24.63 es s pe 1000 people, which seems
o be a good ﬁgu e compa ed o ha o o he coun ies. Howe e , se e al expe s ha e
c i icized he ac ha he es ing le els we e no su ﬁcien o mee he need o a g adual
eopening by 1 May 2020 [
27
]. In addi ion, exis ing ﬂaws in o he esponse s a egies also
blocked imp o emen s in he e ﬁciency ank o he USA. Fo example, he US Cen e s
o Disease Con ol and P e en ion (CDC) emphasized he impo ance o mask-wea ing,
bu Donald T ump con inued o ejec being pho og aphed in public wea ing a mask [
34
].
Some expe s ha e sugges ed ha he guidelines o mask-wea ing ha e been con using.
Thus, many p o es e s ac oss he coun y a e desc ibed as people who e use o wea a
mask [35].
In ac , he USA has no been posi i ely and se iously p epa ed o epidemic mi iga ion
since he ﬁ s conﬁ med case occu ed on 23 Janua y 2020. On 23 Ap il 2020, T ump
sugges ed injec ing a powe ul disin ec an in o co ona i us pa ien s as a possible cu e o
COVID-19. This news esul ed in c i icism om many schola s and epo e s and disbelie
and de ision wo ldwide [36].
The ends in e ﬁciency anks o Type (5) coun ies, including Mexico, Nige ia, and
Saudi A abia, ﬂuc ua ed mo e han hose o he o he coun y ypes. The es ing a e
in Mexico anged om 0.01 o 3.1 es s pe 1000 people du ing he whole pe iod, which
was much lowe han ha in o he coun ies. Thus, he mi iga ion e ﬁciency o Mexico
anked 17 h among he 23 coun ies in S age 5 and S age 6. On 13 June 2020 ( he ﬁnal
day o S age 6 o Nige ia), he es ing a e was 0.44 es s pe 1000 people. Nige ia had a
lowe es ing a e han Mexico, bu he e ﬁciency anks o Nige ia we e no bad. Thus, we
easonably suspec ha he high-e ﬁciency anks o Nige ia may ha e been caused by an
unde es ima ion due o low i al es ing a es.
4.2. The Co ela ion o E ﬁciency Ranks among Va ious S ages
Table 3 indica es ha he co ela ion coe ﬁcien be ween wo adjacen s ages was
highe han ha be ween wo non-adjacen s ages. The co ela ion coe ﬁcien s be ween
S age 1 and each s age a e S age 3 we e low and nega i e. The nega i e o nea -ze o
co ela ion coe ﬁcien s be ween S age 1 and S ages 4–6 imply ha he e ﬁciency anking
o he sampled coun ies a S ages 4–6 had been eo ganized and comple ely di e ed
om ha a S age 1. This implies ha a S age 1, some coun ies s a ed o implemen
e ec i e esponse s a egies such as ex ensi e i al es ing, lockdowns, wea ing o masks,
e c., o p e en he sp ead o COVID-19 and hus c ea ed imp o ed e ec s a S ages 4–6.
In con as , some coun ies pu posely neglec ed he se ious and eme gen impac s a ising
om COVID-19 sp ead and ailed o ake any measu es in esponse o he eme gence o
he epidemic. On he o he hand, he high co ela ion coe ﬁcien s be ween S age 4 and
S age 5, S age 4 and S age 6, and S age 5 and S age 6 imply ha he ela i e e ﬁciency anks
among hese coun ies became s able because hei esponse s a egies had s abilized.
The e ﬁciency anks in some coun ies showed a high deg ee o ﬂuc ua ion ac oss
s ages, especially he Type (5) coun ies. The high ﬂuc ua ion in e ﬁciency anks implied
ha good e ﬁciency ankings a a pa icula s age we e only empo a y and may ha e
de e io a ed in he nex s age. The mi iga ion e ﬁciency ankings o Type (3) coun ies
con inually wo sened om S age 1 o S age 6. Thus, he Type (3) coun ies could no
eco e om he a ack o COVID-19 in a sho ime and would ha e o adop s ic e
esponse policies o mi iga e he sp ead o COVID-19. Type (4) coun ies showed a U-
127
Heal hca e 2021,9, 755
shaped pa e n, demons a ing empo a ily imp o ed anks in he middle s ages, bu
e en ually, he anking eg essed in he ﬁnal s ages.
Bo h he in e ed U-shaped (Type 1) and in e ed N-shaped (Type 2) pa e ns in he
ends in e ﬁciency anks seemed o be a good sign o imp o emen , as he e ﬁciency anks
inc eased in he las s ages. The p obabili y o eco e ing om he a ack o COVID-19 o
Type (1) and (2) pa e ns is highe han ha o o he pa e ns. Ne e heless, he o e all
e ﬁciency was calcula ed based on he whole pe iod co e ing 105 days since he ﬁ s
conﬁ med case. The e ﬁciency ob ained was only empo a y and could change o he
be e o wo se i he assessmen s age was ex ended o co e mo e days.
4.3. The Epidemic S abili y
A he beginning o June 2020, he in ec ious disease COVID-19 emained a high isk
in he wo ld, bu many coun ies ha e since a emp ed o li he s a e o lockdown, es a
he economy, and ake ac ion, as hei go e nmen s ha e conside ed ha he numbe o
conﬁ med cases was g ea ly educed and ha newly diagnosed cases may be conside ed
spo adic cases. Fo example, T ump a emp ed o end he lockdown and he s ay-a -home
o de and o eopen schools a he beginning o June 2020 [37].
The e was a high co ela ion be ween he e ﬁciency sco es in wo adjacen s ages, bu
i was s ill di ﬁcul o p edic he epidemic s abili y o he nex s age based on ha o he
p e ious s age. Thus, he da a o he newly conﬁ med cases o he cu en da es a e only
o e e ence o de e mine he iming o es a ing he economy. This pape sugges s ha
an epidemic s abili y indica o in combina ion wi h a end pa e n o e ﬁciency anks such
as Type (1) o (2) may be employed o judge he app op ia eness o any measu es o ease
he esponse s a egies such as a el es ic ions, s ay-a -home o de s, and mask-wea ing.
Low alues o epidemic s abili y imply ha he end ega ding he epidemic has
a ained a s able s a e and app oached ze o conﬁ med cases. Thus, China, Japan, Ko ea,
and Aus alia seem o ha e eco e ed om he a ack o COVID-19, while B azil, Saudi
A abia, Sou h A ica, and he USA emain engaged in he ba le agains COVID-19 and a e
equi ed o de o e mo e e o o c ea e new oppo uni ies. On 27 June 2020, China, Japan,
Ko ea, and Aus alia had 24, 100, 51, and 37 daily new conﬁ med cases [
1
], espec i ely,
being much lowe han he peak o daily new conﬁ med cases o each coun y. In con as ,
a he end o June 2020, B azil and he USA con inually se new eco ds o daily new
conﬁ med cases. The numbe o newly conﬁ med cases on 27 June 2020 was 39,483, 3938,
6215, and 40,526 cases o B azil, Saudi A abia, Sou h A ica, and he USA, espec i ely [
1
].
On 30 June 2020, he Eu opean Council announced he easing o a el es ic ions
om 1 July 2020 o esiden s o ecommended coun ies, including Aus alia, Japan, Ko ea,
China, and Canada [
38
]. As indica ed in Table 4, China, Japan, Ko ea, and Aus alia anked
ﬁ s o ou h in epidemic s abili y. Canada was sligh ly behind in 13 h place. To examine
he app op ia eness o li ing he a el es ic ions a he ex e nal bo de s o esiden s
o hese coun ies, we used he da a o 27 June 2020 as an example. On ha day, he
numbe o newly conﬁ med cases in China, Japan, Ko ea, Aus alia, and Canada was 24,
100, 51, 37, and 380, espec i ely, equi alen o a s abili y o 0.0168, 0.791, 0.995, 1.451,
and 10.068 cases pe million pe day. The ES on 27 June 2020 in China, Japan, Ko ea, and
Aus alia was much lowe han he alue o Ge many’s ES (Table 4). This implies ha
he sp ead o COVID-19 had been con olled in hese coun ies and was mo e s able han
in Ge many. The ES alue on 27 June 2020 o Canada was nea ly he same as ha o
F ance, as indica ed in Table 4. Howe e , Canada showed a U-shaped pa e n o he end
in e ﬁciency anks, and i is sugges ed ha he EU wai and obse e he e ﬁciency end
and he newly conﬁ med cases o Canada. Thus, he esul s sugges ha he li ing o
a el es ic ions o hese coun ies, wi h he excep ion o Canada, is qui e easonable
based on he indica o o epidemic s abili y and he ends in e ﬁciency anking p esen ed
in his pape .
128
Heal hca e 2021,9, 362
as well as he mechanism o ac ion in he elde ly and hose su e ing om unde lying
heal h condi ions [
5
]. Addi ionally, he sudden eme gence o nume ous s ains wo ldwide,
such as he B.1.1.7 (Uni ed Kingdom) and B.1.1.28 (Sou h A ica) linages, added o hei
di e gen mu a ions, he li le known in o ma ion abou hei se e i y, ansmission, and
esis ance ha e all pu he a e o he newly p oposed ea men s and accines a s ake [
6
,
7
].
In addi ion o he igh ening in ec ion and dea hs wo ldwide, COVID-19 has aken
i s oll on he global economy. Wi h inc easing in ec ions and mul iple o ced lockdowns,
many businesses, manu ac u ing companies, and o ganiza ions educed hei ac i i ies,
sales, and o e all p oduc ions, which, in u n, slowed down he global economy un il i
almos came in o a “ eeze” [
8
]. The global economic knockou has d as ically a ec ed
heal hca e wo ke s, pa icula ly he adiology depa men . Wi h he inc easing need o
in ensi e ca e uni (ICU) beds, medica ions, and pe sonal p o ec i e equipmen (PPE) on
one hand, and he educ ion in admissions on he o he hand due o ea o con ac ing
he i us, hospi als a e s uggling o main ain hei e enues [
9
]. Radiology depa men s
wo ldwide a e expe iencing a signiﬁcan d op in imaging olumes, especially sc eening
se ices o b eas and lung cance , a e he Ame ican College o Radiology (ACR) and
Cen e s o Disease Con ol and P e en ion (CDC) implemen ed se e al guidelines, some
o which included pos poning and escheduling non-u gen pa ien isi s [10].
As o Lebanon, a 10,452 Km
2
coun y loca ed in he Middle Eas , he ba le wi h
con olling he i al sp ead is s enuous. Wi h he ﬁ s COVID-19 in ec ion epo ed on
21 Feb ua y 2020, Lebanon has aced many obs acles ha hinde ed he abili y o slow he
sp ead o he i us among i s inhabi an s [
11
]. Despi e he ac ha Lebanon was no he
pionee in heal hca e acco ding o he WHO’s epo in 2000, holding he ank 91 [
12
],
he coun y unde wen a ious changes, e o ms, and ad ancemen s o be anked as he
23 d coun y wo ldwide in 2018 acco ding o Bloombe g’s Heal hca e E ﬁciency Index [
13
].
Howe e , acco ding o he same index, he coun y has la e on declined and anked 48 h in
2020 amid he pandemic, since Lebanon was less p epa ed o such a pandemic compa ed
o o he coun ies. Un o una ely, his e ﬁcien heal hca e sys em is no ee o i s ci izens.
This has led many Lebanese people su e ing om COVID-19 symp oms o skip pe o ming
necessa y diagnos ic es s and a oid hospi al admission simply because hey canno a o d
he cos . In addi ion, in spi e o ha ing some o he mos ad anced hospi als, Lebanon,
like many o he coun ies, was no p epa ed o such pandemic due o he limi ed numbe
o beds in he ICUs and he signiﬁcan sho age in en ila o s. The e o e, in spi e o all
e o s o “ﬂa en he cu e”, Lebanon has eco ded an exponen ial d as ic inc ease in he
daily numbe o cases and dea hs. The eason behind ha was he massi e explosion ha
occu ed a he Po o Bei u on 4 Augus 2020. The explosion killed o e 200 people,
inju ed mo e han 6000 o he s, and le a ound 300,000 people homeless [
14
], causing
chaos in hospi als as well as a spike in he epo ed COVID-19-posi i e cases. Following
he explosion, a ious essen ial hospi als in he capi al we e comple ely des oyed, hus
pu ing mo e weigh on he medical s a , especially he adiology depa men .
On op o ha , due o poli ical p oblems, Lebanon is su e ing om a c i ically de e i-
o a ing economic c isis. The na ional cu ency, he Lebanese pound (LBP), is alling s i
agains he Uni ed S a es dolla (USD). I los abou 80% o i s alue, hus causing a se e e
inﬂa ion in he coun y [
15
]. Wi h inﬂa ion eaching e i yingly high le els, Lebanon is
cu en ly anked second wo ldwide in e ms o hype inﬂa ion acco ding o he Hanke’s
Annual Inﬂa ion Ra e model [
16
]. Besides inc easing po e y le el o 55% (compa ed o
28% in 2019) [
17
], his inﬂa ion nega i ely impac s he heal hca e sys em as all p oduc s
needed a e impo ed in o eign cu ency (i.e., USD o EUR). Mos heal hca e ins i u ions in
he coun y a e p i a e hospi als and/o medical cen e s and labo a o ies. The e o e, he e
is a huge di ﬁcul y in coping wi h he inc easing p ices o ma e ials and equipmen , hus
posing a isk o he s a ’s heal h and sa e y as ins i u ions adminis a o s can no longe
a o d adequa e and/o good quali y PPE and disin ec ing/cleaning agen s. This inc eases
he h ea o heal hca e membe s, especially adiog aphe s, o con ac ing he i us om
he wo kplace and ansmi ing i o hei amily and/o lo ed ones. The wo sening eco-
135

Heal hca e 2021,9, 362
nomic si ua ion does no only s ike he heal hca e sys ems and s a in Lebanon ﬁnancially,
bu also d ains hem o all ene gy and hospi al beds by escala ing he daily numbe o
COVID-19- epo ed cases. Lebanese people a e o ced o b eak all lockdown ules and
open hei shops/businesses in o de o pu ood on hei ables and eed hei amilies,
a phenomenon accompanied by he absence o social dis ancing and p ecau ions, hus
eﬂec ing a soa in COVID-19 cases and mo e p essu e on he heal hca e sys em.
Following in e na ional guidelines, ho acic imaging, especially ches adiog aphy
and ches Compu ed Tomog aphy (CT), a e being labo iously used in all hospi als and
imaging cen e s in Lebanon as powe ul ools o he diagnosis, de ec ion o complica ions,
and ollow-up o COVID-19 pa ien s [
18
]. Va ious s udies ha e p o en he impo ance
o ches CT in de ec ing SARS-CoV-2 in pa ien s wi h nega i e e e se ansc ip ion poly-
me ase chain eac ion (RT-PCR) esul s [
19
]. One s udy in ol ing 1014 pa ien s showed
ha ches CT scan had a highe sensi i i y (97%) compa ed o RT-PCR [
20
]. In addi-
ion, a ecen s udy p o ed he p ac icabili y o magne ic esonance imaging (MRI) in
he de ec ion o pulmona y changes and damage caused by COVID-19, hus p oposing a
po en ial adia ion- ee al e na i e o ches CT, especially when pe iodic, epe i i e scans
a e equi ed o ollow-up [
21
]. Fu he mo e, he newly eme ging a iﬁcial in elligence
(AI)-based algo i hms ha ha e he abili y o de ec COVID-19 pneumonia on ches CT
wi h app oxima ely 90.8% accu acy, 84% sensi i i y, and 93% speciﬁci y [
22
], can conse-
quen ly enhance he pa amoun ole adiog aphe s and medical imaging play du ing he
COVID-19 pandemic.
The huge wo kload on adiology depa men s in Lebanon, speciﬁcally on Lebanese
adiog aphe s o adiologic echnologis s, due o he ongoing pandemic, as well as he
wo sening economic si ua ion, ha e led o many ad e se e ec s such as i egula and
dis u bed shi s, loss o wo k, inc eased adia ion exposu e, de e io a ing men al and
physical heal h. The e a e cu en ly no s udies conduc ed in he egion o poin ou he
c i ical si ua ion adiog aphe s o adiologic echnologis s a e going h ough. This s udy
aimed o shed ligh on wha he on line he oes a e going h ough in he mids o all
hese unp eceden ed c ises, and e alua e ac o s associa ed wi h s ess om con ac ing
he COVID-19 i us om he wo kplace among adiog aphy echnicians.
2. Me hods
2.1. S udy Design
A c oss-sec ional s udy was conduc ed among adiog aphe s o adiologic echnolo-
gis s egis e ed in he Lebanese Socie y o Radiog aphe s (LSR) in mul iple hospi als and
medical cen e s all o e he coun y. They we e eques ed o ﬁll ou an elec onic su ey
speciﬁcally ailo ed o inqui e how he pandemic a ec ed hem, hei wo k, and hei
o e all wellbeing, di ec ly and indi ec ly. The s udy was conduc ed om 3 Decembe 2020
un il 17 Decembe 2020.
2.2. Minimal Sample Size Calcula ion
On he basis o a popula ion size o 325 ac i e adiog aphy echnicians, and a 75.4%
expec ed equency o wo kplace- ela ed s ess a e he ou b eak [
23
], we ound ha he
minimal sample size needed o bi a ia e and mul i a iable analysis was 152 acco ding o
he Epi-in o so wa e (Cen e s o Disease Con ol and P e en ion, A lan a, GA, USA) [
24
].
2.3. Ques ionnai e and Va iables
The online su ey, p oposed in 3 languages (English, A abic, and F ench), was dis-
ibu ed o all LSR egis e ed membe s ia he social ne wo k pla o ms (i.e., o ﬁcial
Wha sApp g oups o he syndica e). The su ey was composed o 26 ques ions o ganized
in o 6 sec ions (gene al, wo kplace condi ions, heal h and sa e y, men al/psychologic,
ﬁnancial, and skill/knowledge de elopmen ques ions). The ﬁ s sec ion aimed o s udy
he demog aphical and educa ional s a us o he adiog aphe s: age, gende , ma i al s a us,
deg ee, and wo kplace ype. The second sec ion aimed o assess he changes made in
136
Heal hca e 2021,9, 362
he wo kplace: a iabili y in shi s, o e all changes in depa men wo kload, wo kﬂow,
p o ocols, and sa e y measu es (PPE use, disin ec ion, compulso y mask use). The nex
sec ion discussed he impac o he i us on echnologis s’ heal h and sa e y wi h ques ions
e alua ing whe he hey ha e con ac ed he i us, i s se e i y, i s ansmission, and he
need o any hospi al admission. The ollowing sec ion analyzed he men al o psychologic
ou come, wi h ques ions inqui ing abou he p esence and se e i y o wo kplace- ela ed
s ess, i s impac on hem and hei amily/lo ed ones, and he suppo ecei ed. The ﬁ h
sec ion aimed o de e mine he ﬁnancial impac o he pandemic on Lebanese adiog a-
phe s by including ques ions conce ning he mon hly sala y, he ex en o modiﬁca ions
done o ha sala y, and whe he he adiog aphe s a e conside ing qui ing hei jobs.
The las sec ion es ima ed a a he posi i e impac o he pandemic, especially du ing he
lockdown pe iods and dec eased shi s, in e ms o skills and/o knowledge de elopmen
wi h ques ions e alua ing he use o ee ime in beneﬁcial, ec ea ional ac i i ies and he
p e e ed ype o ac i i ies.
2.4. S a is ical Analysis
Desc ip i e, bi a ia e, and mul i a iable s a is ical analyses we e conduc ed using
S a is ical Package o he Social Sciences (SPSS) .25 (A monk, NY, USA). The quan i a i e
a iables we e exp essed as pe cen ages and compa isons we e made using he chi-squa ed
es . A mul inomial eg ession was conduc ed, aking he s ess/wo y abou con ac ing
COVID-19 om he wo kplace ca ego ies (s ongly disag ee/disag ee, ag ee/s ongly
ag ee, and neu al) as he dependen a iable. The neu al g oup was aken as e e ence.
The Nagelke ke pseudo R
2
alues we e also calcula ed o de e mine he a iance explained
by each independen a iable o he ou come a iable. Signiﬁcance was se a p< 0.05.
3. Resul s
A o al o 212 su ey esponses ha accoun ed o 32.5% o o e all egis e ed adiologic
echnologis s o 65.3% o ac i e membe s was ecei ed. Ou o he h ee su ey languages
a ailable, he A abic language was p e e ed by almos 46.23% (n= 98) o adiog aphe s,
hen he English language wi h 39.62% (n= 84) submissions, ollowed by he F ench
language wi h 14.15% (n= 30) submissions (Figu e 1). As o he es o he su ey
ques ions, he esul s o he h ee su ey languages we e combined.
Figu e 1.
Pie cha showing he pe cen age dis ibu ion o he h ee languages: English, A abic, and
F ench ( he pe cen ages we e ounded o he nea es whole numbe ).
3.1. Gene al Ques ions
Responses we e ecei ed mainly om adiog aphe s ha belonged o he 20–29 age
g oup (47.17%) and he 30–39 age g oup (31.13%), while only 1.89% o adiog aphe s we e
137
Heal hca e 2021,9, 362
abo e 60 yea s old. Conce ning he gende dis ibu ion o adiog aphe s, esponses we e
almos equally dis ibu ed be ween males and emales, wi h he pe cen age o males being
sligh ly g ea e han ha o emales (51.42% s. 48.58%, espec i ely). As o he ma i al
s a us, esul s showed ha 52.36% o pa icipan s we e ma ied, 38.21% we e single, 8.02%
we e engaged, and only 1.41% we e di o ced. Conce ning he highes deg ee in he ﬁeld,
pa icipan s held a T.S./L.T. ( echnical deg ees) in Radiog aphy wi h 36.32% submissions,
16.98% had a uni e si y diploma, 33.96% ea ned hei Bachelo o Science (B.S.) deg ee,
8.02% had a Mas e o Science (M.S.) deg ee, and only 4.72% chose he “o he ” op ion and
elied mainly on p ac ical expe ience. Rega ding he dis ibu ion o wo k loca ions, mos o
he pa icipan s (71.23%) wo ked in p i a e hospi als, 14.62% in imaging cen e s, and only
10.83% in public hospi als. Table 1 summa izes he ques ions, answe s, and pe cen ages o
his sec ion.
Table 1.
Table summa izing he ques ions, choices, and pe cen ages conce ning he gene al
ques ions sec ion.
Ques ion Choices and Pe cen ages
Age 20–29
47.17%
30–39
31.13%
40–49
11.79%
50–59
8.02%
60+
1.89%
Gende Males
51.42%
Females
48.58%
Ma i al
S a us
Single
38.21%
Engaged
8.02%
Ma ied
52.36%
Di o ced
1.41%
Highes
Deg ee
T.S./L.T.
36.32%
Diploma
16.98%
B.S.
33.96%
M.S.
8.02%
O he s
4.72%
Wo k
Loca ion
P i a e Hospi al
71.23%
Public Hospi al
10.85%
Lab/Medical Imaging
Cen e
14.62%
O he s
3.30%
3.2. Wo kplace Condi ions du ing he Pandemic
A o al o 69.81% o pa icipan s ag eed ha he wo kload in he depa men was
a ec ed by he pandemic (ag ee (45.28%), s ongly ag ee (24.53%)). Simila ly, he highes
pe cen age o pa icipan s (58.49%) ag eed (ag ee (37.74%), s ongly ag ee (20.75%)) ha
hei shi du a ion and dis ibu ion we e impac ed by he pandemic. While o ing o he
modali y ha ecei ed he mos wo kload, he mos selec ed choices we e CT and X- ay,
wi h 47.87% and 38.53%, espec i ely. Pa icipan s we e gi en he chance o selec mo e
han one op ion esul ing in a o al o 353 o es, 169 o CT and 136 o X- ay. When asked
whe he he ins i u ion is applying an adap ed sa e y p o ocol o COVID-19 pa ien s,
67.45% o o es ag eed (ag ee (47.17%), s ongly ag ee (20.28%)). In he same sense, mos
adiog aphe s ag eed ha hei ins i u ion is p o iding PPE and/o cleaning/disin ec ing
agen s wi h a ound 69.81% o he o es (ag ee (43.87%), s ongly ag ee (25.94%)). Likewise,
88.68% o he pa icipan s ag eed (ag ee (32.08%), s ongly ag ee (56.60%)) ha hei
ins i u ion is o cing all pa ien s, isi o s, and s a o wea ace masks. Figu e 2 summa izes
he ques ions, answe s, and pe cen ages o his sec ion.
138
Heal hca e 2021,9, 362
Figu e 2. Pie cha s summa izing he ques ions, choices, and pe cen ages conce ning he wo kplace condi ions sec ion.
3.3. Heal h and Sa e y
Responses showed ha 64.15% o adiog aphe s disag eed (disag ee (25.00%), s ongly
disag ee (39.15%)) ha hei ins i u ion is p o iding egula /pe iodic, ee PCR es ing o
he s a , while only 25.94% ag eed. The highes pe cen age o pa icipan s 74.53% did no
con ac he i us. Ou o he 12.26% adiog aphe s who caugh he i us, 61.54% go i
om he wo kplace, 34.62% su e ed om mild symp oms, and 92.31% we e no admi ed
o he hospi al. Only 30.77% o in ec ed adiologic echnologis s ansmi ed he i us
o amily membe s/ iends/colleagues, while 50.00% did no , and 19.23% we e no su e.
Table 2 summa izes he ques ions, answe s, and pe cen ages o his sec ion.
139
Heal hca e 2021,9, 362
Table 2. Table summa izing he ques ions, choices, and pe cen ages conce ning he heal h and sa e y sec ion.
Ques ion Choices and Pe cen ages
My ins i u ion is p o iding
egula /pe iodic, ee PCR
es ing o s a .
S ongly Disag ee
39.15%
Disag ee
25.00%
Neu al
9.91%
Ag ee
16.04%
S ongly Ag ee
9.90%
Ha e you con ac ed
he i us?
Yes
12.26%
No
74.53%
I am no su e
13.21%
Is i om he wo kplace? Yes
61.54%
No
11.54%
I am no su e
26.92%
Wha was he se e i y o
he disease?
No symp oms
7.69%
Mild symp oms
34.62%
Mode a e symp oms
30.77%
Se e e symp oms
26.92%
We e you admi ed o
he hospi al?
Yes
8.02%
No
25.94%
Did you ansmi he i us o
any amily
membe / iend/colleague?
Yes
30.77%
No
50.00%
I am no su e
19.23%
3.4. Financial Ques ions
Pa icipan s we e asked o gi e an es ima e (in LBP) o hei o iginal mon hly sala y
p o ided by he ins i u ion, acco ding o he wo k con ac (Figu e 3).
Figu e 3. Ba g aph p esen ing he pe cen ages o sala y anges as disclosed by he pa icipan s.
While 60.85% o adiologic echnologis s had no change in hei sala y, 30.19% dis-
closed ha hey had 25–50% o e en mo e han 50% educ ions in hei sala y, whe eas
4.24% we e no ge ing paid hei mon hly sala y. Mo eo e , 61.11% o pa icipan s dis-
ag eed (disag ee (36.42%), s ongly disag ee (24.69%)) on lea ing hei job/s aying home,
while 35.80% had a di e en opinion. Table 3 summa izes he ques ions, answe s, and
pe cen ages o his sec ion.
140

Heal hca e 2021,9, 362
Table 3. Table summa izing he ques ions, choices, and pe cen ages conce ning he ﬁnancial ques ions sec ion.
Ques ion Choices and Pe cen ages
To wha ex en did he
ins i u ion
modi y/dec ease he
mon hly sala y p o ided
o you in acco dance
wi h he economic
si ua ion?
Se e ely
(>50% educ ion)
6.13%
Mode a ely
(25–50% educ ion)
24.06%
No Change
60.85%
My sala y was
modiﬁed bu wha
was educed will
be paid la e on
4.72%
I am no ge ing
paid my
mon hly sala y
4.24%
I am conside ing lea ing
job/s aying home, as i
is no wo h i .
S ongly Disag ee
24.69%
Disag ee
36.42%
Neu al
3.09%
Ag ee
25.31%
S ongly Ag ee
10.49%
3.5. Men al/Psychological Ques ions
Conce ning men al/psychological ques ions, 60.85% o adiog aphe s ag eed (ag ee
(35.85%), s ongly ag ee (25.00%)) ha hey we e eeling s essed/wo ied abou con ac -
ing he i us om he wo kplace. Simila ly, 67.92% ag eed (ag ee (45.75%), s ongly ag ee
(22.17%)) ha hei amily membe s, iends, and/o lo ed ones we e a ec ed by his wo k-
ela ed s ess. Fu he mo e, 43.86% o su eyo s disag eed (disag ee (20.75%), s ongly
disag ee (23.11%)) ha hei ins i u ion is showing adequa e social, psychological, and/o
ﬁnancial ca e/ ollow up o s a membe s who con ac ed he i us. Hal o he pa ici-
pan s disag eed (disag ee (25.47%), s ongly disag ee (24.53%)) abou hinking/planning
o change he ﬁeld o wo k and lea e he heal hca e sys em; 69.81% o esponde s ag eed
(ag ee (25.00%), s ongly ag ee (44.81%)) abou lea ing he coun y o seek a be e oppo u-
ni y ab oad, while only 16.04% o ed o he opposi e. Figu e 4 summa izes he ques ions,
answe s, and pe cen ages o his sec ion.
3.6. Skill/Knowledge De elopmen
Mo e han hal o he pa icipan s (65.09%) used hei ee ime du ing he lockdown o
skill de elopmen and/o knowledge expansion. Nume ous op ions we e selec ed ega ding
he kind o ac i i ies done, and many o he pa icipan s chose he “o he ” op ion. Fo
simplici y, he kinds o ac i i ies done a e summa ized in he ba g aph below (Figu e 5).
3.7. Bi a ia e Analysis
A signiﬁcan ly highe pe cen age o pe sons who had a neu al opinion abou he
wo kload being a ec ed by he pandemic ag eed/s ongly ag eed ha hey a e s essed
and wo ied abou con ac ing COVID-19 om he wo kplace (Table 4). No signiﬁcan
associa ion was ound be ween all o he a iables and he s ess/wo y abou con ac ing
COVID-19 om he wo kplace.
141
Heal hca e 2021,9, 362
Figu e 4.
Pie cha s summa izing he ques ions, choices, and pe cen ages conce ning he men-
al/psychological ques ions sec ion.
Figu e 5.
Ba g aph summa izing he a ious ypes o ec ea ional ac i i ies done by he pa icipan s
du ing hei ee ime in he lockdown.
142
Heal hca e 2021,9, 362
Table 4. Bi a ia e analysis o ac o s associa ed wi h s ess ca ego ies.
Va iable S ess/Wo y abou Con ac ing COVID-19 om he Wo kplace p
Neu al S ongly Disag ee/Disag ee Ag ee/S ongly Ag ee
Age ca ego ies (in yea s) 0.145
20–29 27 (26.5%) 22 (21.6%) 53 (52.0%)
30–39 16 (24.2%) 9 (13.6%) 41 (62.1%)
40–49 4 (16.0%) 3 (12.0%) 18 (72.0%)
50 and abo e 1 (4.8%) 3 (14.3%) 17 (81.0%)
Gende 0.238
Male 29 (26.6%) 20 (18.3%) 60 (55.0%)
Female 19 (18.1%) 17 (16.2%) 69 (65.7%)
Ma i al s a us 0.841
Single/engaged/di o ced 25 (24.3%) 17 (16.5%) 61 (59.2%)
Ma ied 23 (20.7%) 20 (18.0%) 68 (61.3%)
Wo kload a ec ed by he pandemic 0.034
S ongly disag ee/disag ee 12 (29.3%) 6 (14.6%) 23 (56.1%)
Neu al 0 (0%) 5 (21.7%) 18 (78.3%)
Ag ee/s ongly ag ee 36 (24.0%) 26 (17.3%) 88 (58.7%)
Shi du a ion dis ibu ion impac ed
du ing he pandemic 0.204
S ongly disag ee/disag ee 12 (23.5%) 4 (7.8%) 35 (68.6%)
Neu al 8 (21.6%) 5 (13.5%) 24 (64.9%)
Ag ee/s ongly ag ee 28 (22.2%) 28 (22.2%) 70 (55.6%)
Ins i u ion applies adap ed sa e y
p o ocol 0.268
S ongly disag ee/disag ee 4 (15.4%) 2 (7.7%) 20 (76.9%)
Neu al 8 (18.6%) 6 (14.0%) 29 (67.4%)
Ag ee/s ongly ag ee 36 (24.8%) 29 (20.0%) 80 (55.2%)
Ins i u ion supplying cleaning agen s 0.224
S ongly disag ee/disag ee 4 (17.4%) 4 (17.4%) 15 (65.2%)
Neu al 6 (14.6%) 4 (9.8%) 31 (75.6%)
Ag ee/s ongly ag ee 38 (25.3%) 29 (19.3%) 83 (55.3%)
Ins i u ion o ces mask wea ing 0.083
S ongly disag ee/disag ee 4 (36.4%) 0 (0%) 7 (63.6%)
Neu al 0 (0%) 2 (15.4%) 11 (84.6%)
Ag ee/s ongly ag ee 44 (23.2%) 35 (18.4%) 111 (58.4%)
Numbe s in bold indica e signiﬁcan p- alues.
3.8. Mul i a iable Analysis
The esul s o he eg ession, aking s ess/wo y abou con ac ing COVID-19 om
he wo kplace (ag ee/s ongly disag ee s. neu al*) as he dependen a iable, showed
ha ha ing 50 o mo e yea s s. 20–29 yea s (adjus ed odds a io (aOR) = 9.53; p= 0.036)
was signiﬁcan ly associa ed wi h highe odds o ag eeing/s ongly ag eeing abou ha ing
s ess/wo y abou con ac ing COVID-19 om he wo kplace (Table 5).
Table 5. Mul inomial eg ession.
S ess/Wo y Abou Con ac ing COVID-19 om he Wo kplace (Ag ee/S ongly Ag ee s. Neu al)
Va iable aOR p95% CI
Age ca ego ies (in yea s) 0.182
20–29 1
30–39 1.28 0.531 0.59–2.79
40–49 1.69 0.407 0.49–5.81
50 and abo e 9.53 0.036 1.16–78.30
Numbe s in bold indica e signiﬁcan p- alues.
143
Heal hca e 2021,9, 362
None o he a iables we e signiﬁcan ly associa ed wi h disag eeing/s ongly dis-
ag eeing abou ha ing s ess/wo y abou con ac ing COVID-19 om he wo kplace
compa ed o neu al.
Va iables en e ed in he model: wo kload a ec ed by he pandemic, ins i u ion o ces
mask wea ing, age ca ego ies (Nagelke ke pseudo R
2
= 21.3%); Nagelke ke pseudo R
2
o
he a iable wo kload a ec ed by he pandemic = 6.9%; Nagelke ke pseudo R
2
o he
a iable ins i u ion o ces mask wea ing = 6.4%; Nagelke ke pseudo R
2
o he a iable age
ca ego ies = 6.8%; numbe s in bold indica e signiﬁcan p- alues (p< 0.05).
4. Discussion
Radiology, especially ches X- ay and CT examina ions, has played a c ucial ole
and p o en i s e ec i eness in he diagnosis and ollow-up o pneumonia in COVID-19
pa ien s, in addi ion o assessing be e ea men p o ocols, including measu emen o
disease changes and p edic ing p ognosis [
25
]. Radiologic echnologis s s and equal o, and
side by side wi h, all doc o s and nu ses who a e ﬁgh ing hand-in-hand in his pandemic,
dese ing he i le “ on line he oes”. Wi h he adiology depa men being he p ima y
des ina ion o all Eme gency Room (ER) pa ien s su e ing om espi a o y p oblems and
suspec ed o be COVID-19-posi i e, he adiog aphe s’ oles and di ec con ac wi h hese
pa ien s weigh no less han hose o hei medical colleagues.
This dis inc i e s udy is he ﬁ s o i s kind in he egion and aimed o assess he di ec
and indi ec impac o he ongoing COVID-19 pandemic on adiog aphe s in a coun y
se e ely a ec ed by he COVID-19 pandemic, in addi ion o poli ical and economic c isis.
Mos adiologic echnologis s in he coun y a e ela i ely young (belonging o he
20–29 age g oup), wi h he gende s almos equally dis ibu ed be ween males and emales.
Ins i u ions all o e he coun y a e acing a dec ease in imaging olumes, as shown
by he la ge numbe o adiog aphe s who ag eed/s ongly ag eed ha he wo kload
in hei depa men and shi s we e impac ed. Simila ly, many hospi als and imaging
cen e s a ound he globe ha e also seen signiﬁcan d ops in non-u gen ou pa ien isi s,
imaging, and se ices, e en below baseline alues. Ne e heless, ho acic imaging olumes
in ol ing X- ay and CT we e no se e ely impac ed by he pandemic [
26
]. The esul s
clea ly show he i al ole o X- ay and CT scan in his managemen , as hey ecei ed
he g ea es amoun o o es ega ding he modali ies, wi h mos wo kload eﬂec ing he
impo an ole o ho acic imaging in managing pa ien s du ing he pandemic by de ec ing
signs o COVID-19 pneumonia [
27
]. Mos heal hca e sys ems a e implemen ing and
adap ed sa e y p o ocol when dealing wi h COVID-19 pa ien s and a e supplying he s a
wi h he app op ia e PPEs (i.e., masks, ace shields, glo es, e c.) and cleaning/disin ec ing
agen s. The s ic ules conce ning he compulso y use o ace masks by pa ien s, isi o s,
and s a also eﬂec he e ﬁciency o ins i u ions’ e o s in con olling disease sp ead, a
i al s a egy ha is implemen ed a ound he globe o disease handling and p o ec ion
o he s a om in ec ions [
28
]. P o en e ec i e, a e y high numbe o pa icipan s did
no con ac he i us. Those who did, on he o he hand, su e ed om mild o mode a e
symp oms and did no equi e hospi al admission.
As o he ﬁnancial aspec , he median mon hly income o he Lebanese adiog aphe s
is 1661,125 LBP, which is ela i ely low compa ed o he high hype inﬂa ion le els he coun-
y is su e ing om and he all o he Lebanese cu ency compa ed o o eign cu encies,
especially in black ma ke s. The adiog aphe ’s a e age mon hly sala y ha used o be
equi alen o a ound 1096 USD p e-hype inﬂa ion (o ﬁcial exchange a e 1 USD = 1515 LBP)
now ba ely equals 144 USD (black ma ke 1 USD = 11,500 LBP). Despi e he economic c isis,
mo e han hal o he pa icipan s epo ed no change in hei mon hly income, ye a con-
side able numbe o adiog aphe s a e su e ing om a 20 o 50% educ ion in hei sala y.
A s uggle ha eﬂec s he ac ha he middle-income le el o he Lebanese popula ion is
sh inking. Rega dless o all challenges and educ ions, adiog aphe s disag eed qui ing
hei job and/o s aying home, as hey s ongly hold on o hei humane ole and li e-sa ing
du ies a all cos s. The p oceeding pandemic has a ec ed Lebanese adiog aphe s, no only
144
Heal hca e 2021,9, 220
awa eness ega ding he pandemic o use p e en ion measu es o he con ain pandemic.
YouTube is conside ed o be he mos inspi ing way o sha e he co ona i us pandemic and
imp o e communi y heal h se ices. Pey a e al. [
11
] conside ed a case o I an’s economy
ha has been nega i ely a ec ed by he co ona i us, and he sizeable numbe o egis e ed
cases is inc easing day-by-day. The I anian go e nmen has wo ked dedica edly o con ain
he co ona i us h ough massi e public educa ion p og ams and elec onic awa eness cam-
paigns, while, on he o he side, he coun y is conduc ing esea ch wo kshops, aining,
and inc easing heal hca e budge s o he con ol he pandemic. The need o wo d-o -
mou h campaigns ega ding co ona i us p e en ion is i al o p omo e coun y esilience.
Sahu [
12
] sugges ed se e al policy measu es o con ain he co ona i us among he s uden s
and eaching/adminis a i e s a , as high isk is associa ed wi h he educa ional ins i u es
h ough close con ac s. As pe WHO guidelines, he closu e o all educa ional ins i u es
is deemed o be desi able o such an indeﬁni e pe iod un il he i us can be con olled
acco dingly. Ne e heless, hese posi i e measu es nega i ely impac he men al heal h
o s uden s and academic s a . Thus, he need o p ope counselling, online eaching
cou ses, assessmen s, and e alua ion is highly desi able in imp o ing s uden s and aca-
demic s a ’s psychological heal h. Bhaleka [
13
] a gued ha he Indian economy was
mainly a ec ed by he co ona i us pandemic due o a andom lockdown in a coun y
ha inc eases he daily wage s’ mise ies, which led o inc easing he sou ce o i us in a
coun y. The COVID-19 a ec s all majo sec o s o he Indian economy, no limi ed o he
labo ma ke , educa ional ins i u es, elec onic comme ce, and o e all economic g ow h.
The high need o s a egic hinking, uniﬁed global policies, sma lockdowns, eme gency
elie packages o he poo labo e , and s able ﬁnancial ma ke s would help con ol o he
co ona i us esou ce ully. Zheng [
14
] sugges ed he need o psychological ea men o
heal hca e wo ke s di ec ly exposed o he co ona i us, and hey a e mo e likely conce ned
abou hei amilies and iends. This amily suppo o heal h ca e wo ke s is desi able
o wo king wi h sound heal h. Sani àdi Toppi e al. [
15
] conﬁned hei ﬁndings on a mo e
impo an aspec o sp eading co ona i us pandemic ela ed o he ai bo ne pa icula e,
p o iding a channel o ca y co ona i us in o he human espi a o y sys em. The u gen
need is o making sus ainable policies o limi pa icula e ma e s and limi he i us
acco dingly. Musselwhi e e al. [
16
] sugges ed ha public anspo a ion could be a ca ie
o co ona i us sp ead, as people a e ei he si ing o s anding in a closed en i onmen ,
while coughing, ouching, and sneezing may ansmi he mic oo ganism om one o
o he s. The doo s, icke machines, windows, ele a o s, sea s, and many o he a eas could
be possible places o he in ec ious disease. Deng and Peng [
17
] ound ha he case- a ali y
a io is mainly e iden wi h he ollowing symp oms o co ona i us, including high e e ,
oo much coughing, sho ness o b ea h, and ches pain, while o he como bidi ies o he
a ali y cases, including high s ess, hea pa ien s, diabe es, ce eb al in a c ion, and ch onic
b onchi is. These heal hca e conce ns ha a e equi ed mo e good policies o educe he
case a ali y a io, while symp oma ic ea men is p o ided o he co ona i us pa ien s
un il he possible medica ion and he accine is no in en ed. Anse e al. [18] conside ed
a panel o 76 coun ies using ime se ies da a om 2010–2019 o e alua e he impac o
COVID-19 measu es on global po e y, and ound ha popula ion densi y, lack o necessa y
sani a ion acili ies, en i onmen al challenges, and dea h by communicable diseases pu
a signiﬁcan bu den on he low-income g oup, which could be minimized by inc easing
public heal hca e expendi u es ac oss coun ies. The need o p o-poo g ow h policies
will suppo he b eakdown o he icious cycle o po e y ha would be u he ansla ed
in o sus ained economic g ow h.
The signiﬁcan discussion ha is based on ea lie li e a u e emphasized he need o
e alua e he possible impac s o COVID-19 measu es on se ices indus ies while using an
agg ega ed wo ld da a le el. Fewe s udies on he s a ed opic gi e oom o in es iga e
o selec he speciﬁed a ea, which would p o ide mo e policy insigh s o analyzing he
se ices indus y’s esponse agains he COVID-19 measu es. The objec i es o he s udy
a e as ollows:
151

Heal hca e 2021,9, 220
(I) To examine he possible impac s o COVID-19 measu es on he global se ices
indus y.
(II) To in es iga e he di ec e ec o communicable diseases, including COVID-19,
on se ices alue-added.
(III) To de e mine he ole o wo d-o -mou h agains he co ona i us pandemic and i s
possible impac on he se ices indus y and
(IV) To obse e he e ec s o lockdown, social dis ancing, p ice con ol, and ﬁnancial
ac i i ies on he se ices indus y.
Di e en coun ies ha e widely adop ed hese measu es agains he co ona i us ha
analyzed in he s udy o he se ices sec o . The s udy used quan ile eg ession es ima es
o analyze he p edic o s’ di e en a ia ions on he esponse a iable a di e en quan iles
dis ibu ion. This echnique is be e in a gi en scena io ha will p o ide obus in e ences.
2. Da a Sou ces and Me hodological F amewo k
The e a e some COVID-19 measu es ha ha e been used o con ol he pandemic a a
global scale, and a ew o hem a e lis ed below, i.e.,
(I) In o ma ion Sha ing: he igh in o ma ion wi h co ec ac s and ﬁgu es a e he
esponsibili y o e e y go e nmen o sha e wi h hei esiden s, while, a an in e na ional
pla o m, he WHO and o he in e na ional agencies ha e o p epa e he policy documen s
ega ding p e en ion om no el co ona i us and sp ead i h ough di e en in o ma ion
channels. The na ional and in e na ional agencies ha e al eady p o ided he igh in o -
ma ion h ough a ious communica ion channels, and i is now a du y o espond o he
gene al masses o ac like a ci ilized pe son. The ‘wo d-o -mou h’ mos ly used he wo d in
ma ke ing he speciﬁed p oduc s whe e in o ma ion is sha ed om one pe son o ano he
h ough o al communica ion [
19
]. The adul li e acy a e played a i al ole in p omo ing
communica ion channels o each he igh cus ome s. Based on he abo e discussion,
his s udy used he adul li e acy a e (% o people ages 15 and abo e) as a co ec a iable
o in o ma ion sha ing abou co ona i us, and conside s i as wo d-o -mou h (as deno ed
by WOM) in o ma ion no el co ona i us among he gene al masses in his s udy. The a-
ionale o using his p oxy is ha he li e a e pe son would e ec i ely use all kinds o
communica ion among agen s. Hence, his p oxy would lea e he impac on he li e a u e
o ne wo k awa eness.
(II) Lockdown: he lockdowns, ei he pa ial o comple e, depend upon he se e i y
o he new co ona i us ou b eak in any coun y. This s a egy used almos e e y coun y
in hei pe spec i es o p e en hei o dina y peoples om he deadly disease. The e -
idence indica es ha lockdown is no success ul in many pa s o he wo ld due o he
high incidence o po e y and hunge , which we e la e unded by he go e nmen ’s
eme gency elie s’ packages o he needy peoples [
20
]. The law en o cemen agencies
played an essen ial ole in lockdown in he ci y, as pe Fede al go e nmen ins uc ions [
21
].
The people did no usually ollow he go e nmen ins uc ions due o igno ance, a lack
o in o ma ion, and o he social issues; o his call, law en o cemen agencies can han-
dle his si ua ion. Thus, his s udy used ‘a med o ces pe sonnel’ (in o al) o a nea by
LOCKDOWN p oxy o es ic ee mobili y. Measu ing “lockdowns” by a med o ces
pe sonnel is used o show a s ingen go e nmen policy ha , using ‘powe and con ol’
o con ain widesp ead co ona i us cases by he o ce ul imposi ion o s anda d ope a ing
p ocedu es (SOPs) ega ding co ona i us p e en ion, likely shows a be e p oposi ion
han he ‘Ox o d s ingency index’ o ‘Google mobili y se ies’.
(III) Social Dis ancing: acco ding o he WHO guidelines ega ding p e en ing and
con olling he co ona i us pandemic, i a oids massi e ga he ings and main ains physical
dis ancing among he esiden s. This s a egy is mos ly applied uni o mly ac oss he
globe. Physical dis ancing helps o minimize he isk o co ona i us incidence as i is a
ansmi ed disease, and i s sp ead om close con ac s [
22
]. The popula ion compac ness
could be one eason ha p o ides a channel o ca y one pe son o ano he [
18
]. This s udy
used ‘popula ion densi y’, as pe squa e km o land a ea, as a nea by p oxy o he so-
152
Heal hca e 2021,9, 220
cial dis ancing (deno ed by SOCDIS) o ob ain some conclusi e ﬁndings in his ega d.
The s udy measu es “social dis ancing” by popula ion densi y, a he han using % o he
u ban popula ion because, he highe he popula ion compac in he coun y, he g ea e
will be he chances o sp ead co ona i us cases, i espec i e o u al and u ban sphe es.
The s udy did no limi popula ion densi y o he u ban popula ion while i used he o e all
popula ion compac ness, as co ona i us cases a e sp eading uni o mly in u al and u ban
egions.
(IV) P ice Con ol: due o he co ona i us ou b eak, he globalized wo ld’s mos
c i ical conce n is he ‘p ice con ol’ o he ood i ems especially. As he news abou he
COVID-19 ou b eak ansmi ed ac oss he globe, mass panic sp ead among o dina y
people, and hey ushed a ood i ems o s o e in hei homes. E e y ime, he go e nmen s
gi e conﬁdence o he amilia people and he p oduce s and e aile s o keep calm and
emain easy so ha ood challenges can be esol ed. In his ega d, go e nmen s make
ood con ol p ice commi ees in a di e en pa o he wo ld o p o ide a ee ﬂow o ood
supply a lowe p ices [
23
]. The p esen s udy used he ‘consume p ice index-inﬂa ion’
(%) as a p oxy o ood p ice con ol in he sense ha he co ona i us pandemic inc eases
he p ices o ood i ems due o he sho age o he ood supply chain. Thus, he need o
assess he p ice hikes can be used h ough CPI alues o making an e ec i e p ice con ol
s a egy.
(V) Financial and Economic Ac i i ies: he ou b eak o no el co ona i us nega i ely
a ec s he global s ock ma ke index. I is c ushed in many pa s o he wo ld, due o
ull a el es ic ions, lockdowns, and o he p e en i e measu es, which di ec ly hi he
local and in e na ional businesses [
24
]. The s udy used ‘b oad money supply’, as % o
GDP and ‘GDP pe capi a’ in cons an 2010 US$ as nea by p oxies o ﬁnancial ac i i ies
(deno ed by FACT) and economic ac i i ies (EACT), espec i ely, o assess he coun y’s
economic and ﬁnancial si ua ion amid he co ona i us pandemic. The a ionale o use
bo h o he ac o s is ha money supply is conside ed o be one o he i al ac o s o
ﬁnancial de elopmen indica o s ha mos ly iewed in he ela ion o COVID-19 pandemic.
Simila ly, economic ac i i ies can be be e checked wi h he coun y’s pe capi a income
ha mainly a ec ed he pandemic ecession. Thus, hese p oxies would be help ul in
acing he eal p oblem o he pandemic ecession ac oss coun ies.
(VI) Causes o Dea h by Communicable Diseases: he s udy used he da a o ‘causes o
dea h by communicable diseases’ (as % o o al) (deno ed by COMD) as a e e ence poin
o analyze he dea h oll by a co ona i us.
(VII) Se ices Value Added: he se ice’s alue added (% o GDP) (as deno ed by
SVAD) comp ises dis ibu i e se ices, p oduce se ices, pe sonal se ices, and social
se ices, which is used in his s udy as a esponse a iable.
The COVID-19 measu es a e conside ed o be explana o y a iables o he s udy,
while he alue o he se ice added is se ed as he explained a iable. The wo ld agg e-
ga ed da a a e used o empi ical analysis, co e ing a pe iod o 1975–2020. The missing
in o ma ion is ﬁlled by he p eceding and succeeding alue o he espec i e a iables
whe e equi ed. The da a we e ob ained om he Wo ld Bank [25].
The s udy beneﬁ ed om he Keynesian heo y o agg ega e demand, which a gued
ha agg ega e demand could be a ec ed by any p e ailing shocks in he economies,
which need o be s abilized h ough economic policies. Simila ly, he COVID-19 c isis is
mo e se e e han he ﬁnancial dep ession o 2008 shocks ha cap u ed he whole wo ld,
which declined wo ld economic g ow h. The COVID-19 c isis has a ec ed he economies’
supply and demand simul aneously; o ins ance, social dis ancing c ea es dis ancing
be ween he one pe son and ano he . I educes p oduc i e labo hou s ha lowe he
supply, which inc eases he ma ginal cos o p oduc ion [
26
,
27
]. Signiﬁcan ly, he se ices
sec o is majo ly a ec ed h ough social dis ancing, as i s closely connec ed wi h he
hospi ali y and ec ea ional ac i i ies ha a e banned due o he high isk o sp eading
COVID-19 cases. Se ices alue-added is a subs an ial pa o economic g ow h, as i s GDP
sha e is mo e han 60% wo ldwide. The se ices sec o is used as a e e ence poin ha
153
Heal hca e 2021,9, 220
analyzed i s pe o mance in he wo ld’s GDP ha is mos a ec ed by COVID-19 pandemic,
which can be iewed by he sugges ed empi ical equa ion, i.e.,
ln(SVAD)=α0+α1ln(COMD)+α2ln(WOM)+α3ln(LOCKDOWN)+α4ln(FACT)+α5ln(EACT)
+α6ln(PCONT)+α7ln(SOCDIS)+ε
∴∂ln(SVAD)
∂ln(COMD)<0, ∂ln(SVAD)
∂ln(WOM)>0, ∂ln(SVAD)
∂ln(LOCKDOWN)<0, ∂ln(SVAD)
∂ln(FACT)<0, ∂ln(SVAD)
∂ln(EACT)<0,
∂ln(SVAD)
∂ln(PCONT)<0, ∂ln(SVAD)
∂ln(SOCDIS)<0.
(1)
whe e SVAD shows he se ices alue-added, COMD shows communicable diseases,
WOM shows wo d-o -mou h, LOCKDOWN shows lockdown, FACT shows ﬁnancial
ac i i ies, EACT shows economic ac i i ies, PCONT shows p ice con ol, SOCDIS shows
social dis ancing, and εshows he e o e m.
Equa ion (1) shows ha he s a ed ac o s inﬂuence se ice alue-added. I is likely
ha he causes o dea h by communicable diseases, including COVID-19, will dec ease
se ice alue-added, whe eas imp o ing he communica ion means o in o ma ion sha ing,
including wo d-o -mou h abou co ona i us pandemic, would be help ul in main aining
se ice alue-added sha e ela i e o GDP. Al hough i is no a o able o he alue o he
unc ions added in managing hei GDP sha e, he empo a y o comple e lockdown is no
a o able. Howe e , i is deemed o be desi able o con ol co ona i us on a global scale.
The ﬁnancial and economic ac i i ies supp essed wi h he COVID-19 pandemic nega i ely
inﬂuenced se ices alue-added. The p ice hikes in ood i ems needed e ﬁcien p ice
con ol o acili a e he needy communi y membe s, which subsidized he se ices sec o
o cha ge a smalle p ice, hus main aining easonable p oﬁ . Finally, social dis ancing
is he emedial measu e o con ain co ona i us; howe e , i nega i ely a ec s se ice
alue-added. Figu e 1 shows he esea ch amewo k o he s udy.
Figu e 1 shows he impac s o COVID-19 measu es on he se ices indus y and
iden iﬁed some signiﬁcan de e minan s ha nega i ely a ec global se ice alue added.
These COVID-19 measu es a e highly equi ed o he con olled pandemic; howe e , i
dec eases se ices sha e ela i e o i s coun y GDP. The ollowing esea ch hypo heses
ha e been de eloped o analyze i du ing es ima ion, i.e.,
Hypo hesis 1 (H1).
Communicable diseases, including COVID-19, will likely dec ease he sha e
o se ices alue-added ela i e o he coun y’s GDP.
Hypo hesis 2 (H2).
Wo d-o -mou h o co ona i us pandemic would likely o be help ul o he
p e en ion o i us and inc eases se ices alue-added, and
Hypo hesis 3 (H3).
Lockdown, popula ion compac ness, and ﬁnancial ins abili y will likely
dec ease se ices sha e in o al GDP.
The s udy u ilized a quan ile eg ession appa a us o ob ain pa ame e es ima es.
I wo ks unde di e en assump ions. I gi es a mo e ending analysis o he said pa-
ame e s a di e en quan iles dis ibu ion, which o he a ailable eg ession appa a uses
would be powe less o pe o m, such as ime-se ies coin eg a ion echniques, ins umen al
eg ession echniques, and obus eg ession. These echniques would pe o m well in
hei domain, bu hese a e ine ec i e in analyzing ending eg ession es ima es o e 10 h
quan iles o 90 h quan iles. The gi en p ocedu e would gi e g ea e le e age o exp ess
he pa ame e es ima es o sound in e ences. Equa ion (2) shows he empi ical illus a ion
o di e en quan iles dis ibu ion o he s a ed pa ame e s o eady e e ence, i.e.,
154
Heal hca e 2021,9, 220
ln (SVAD)τ10 =α0+α1ln (COMD)τ10 +α2ln (WOM)τ10 +α3ln (LOCKDOWN)τ10 +α4ln (FACT)τ10
+α5ln (EACT)τ10 +α6ln (PCONT)τ10 +α7ln (SOCDIS)τ10 +ετ10
;
ln (SVAD)τ25 =α0+α1ln (COMD)τ25 +α2ln (WOM)τ25 +α3ln (LOCKDOWN)τ25 +α4ln (FACT)τ25
+α5ln (EACT)τ25 +α6ln (PCONT)τ25 +α7ln (SOCDIS)τ25 +ετ25
:
ln (SVAD)τ50 =α0+α1ln (COMD)τ50 +α2ln (WOM)τ50 +α3ln (LOCKDOWN)τ50 +α4ln (FACT)τ50
+α5ln (EACT)τ50 +α6ln (PCONT)τ50 +α7ln (SOCDIS)τ50 +ετ50
:
ln (SVAD)τ75 =α0+α1ln (COMD)τ75 +α2ln (WOM)τ75 +α3ln (LOCKDOWN)τ75 +α4ln (FACT)τ75
+α5ln (EACT)τ75 +α6ln (PCONT)τ75 +α7ln (SOCDIS)τ75 +ετ75
:
ln (SVAD)τ90 =α0+α1ln (COMD)τ90 +α2ln (WOM)τ90 +α3ln (LOCKDOWN)τ90 +α4ln (FACT)τ90
+α5ln (EACT)τ90 +α6ln (PCONT)τ90 +α7ln (SOCDIS)τ90 +ετ90
(2)
whe e
τ10
o
τ90
show quan iles eg ession es ima es om 10 h quan iles o 90 h quan ile
dis ibu ion.
Figu e 1. Resea ch F amewo k o he S udy. Sou ce: Au ho ’s ex ac .
155
Heal hca e 2021,9, 220
The s udy u he used impulse esponse unc ion (IRF) and a iance decomposi ion
analysis (VDA) o analyzing he pa ame e es ima es in he o ecas ing amewo k o he
nex en yea ime pe iod.
3. Resul s
Table 2 shows he desc ip i e s a is ics o he candida e a iables. The sha e o se ice
alue ha is added o wo ld GDP has eached a maximum o 65.26%, minimum a 54.24%,
and mean 58.47%. The causes o dea h by communicable diseases, on a e age, a e en e ed
a 27.29% o o al wo ld dea h. Wo d-o -mou h is measu ed by an adul li e acy a e wi h
a minimum alue o 65.19%, a maximum amoun o 87.30%, and an a e age alue o
77.30%. A med o ces pe sonnel a e used as a p oxy o lockdown, which shows ha
he global wo ld needed 25,744,314 a med o ces pe sonnel o keep success ul lockdown
o some speciﬁed a ea on a e age. The ﬁnancial and economic ac i i ies a e measu ed
by b oad money supply and GDP pe capi a, wi h an a e age alue o 92.75% o GDP
and US$8,007.36, espec i ely. The p ice con ol is measu ed by changes in he p ice
le el wi h an a e age alue o 6.39%. Finally, social dis ancing is obse ed by popula ion
compac ness, which has an a e age alue o 45.95 people pe squa e m o land a ea.
The gi en desc ip ions o he candida e a iables showed a end analysis o e he pas
45 yea s.
Table 2. Desc ip i e S a is ics.
Me hods SVAD COMD WOM LOCKDOWN FACT EACT PCONT SOCDIS
Mean 58.47710 27.29407 77.30327 25744314 92.75388 8007.362 6.394944 45.95990
Maximum 65.26177 30.90569 87.30101 30196640 125.0989 10892.00 12.47161 59.63624
Minimum 54.24299 20.17717 65.19396 22209230 62.15986 5681.743 1.431611 31.91508
S d. De . 4.384618 4.428943 7.039300 2934139 18.24449 1571.258 3.560119 8.506539
Skewness 0.212882 −0.521528 −0.341577 −0.087964 −0.073547 0.346740 0.464993 −0.013921
Ku osis 1.326914 1.512059 1.738246 1.402185 2.251956 1.834101 1.970756 1.779506
Sou ce: Wo ld Bank [
25
]. No e: SVAD shows se ices alue-added, COMD shows communicable disease, WOM shows wo d-o -mou h,
LOCKDOWN shows lockdown, FACT shows ﬁnancial ac i i y, EACT shows economic ac i i y, PCONT shows p ice con ol, and SOCIDIS
shows social dis ancing.
Table 3 shows he co ela ion es ima es and ound ha communicable diseases,
including COVID
−
19 and p ice con ol, nega i ely co ela e wi h se ice alue-added.
In con as , he o he a iables, including wo d-o -mou h, lockdown, ﬁnancial and eco-
nomic ac i i ies, and social dis ancing, posi i ely associa e se ices alue-added. The esul
implies ha se ices alue-added exposed an inc eased isk o co ona i us pandemic,
while s ic p ice con ol u he dec eases se ices alue-added ac oss he globe. The go -
e nmen ’s measu es o con olled co ona i us would be p ima ily suppo ed se ices alue
added o un hei businesses du ing a elaxed ime as pe go e nmen s’ p o ision o
open hei ma ke s. The wo d-o -mou h o co ona i us pandemic o he gene al masses
would help keep esiden s a hei homes o become sa e om he i us, while, o success-
ul ope a ing lockdowns, he inc easing numbe o a med o ces pe sonnel is desi able.
Financial and economic ac i i ies allow gene al masses o s a hei businesses unde s ic
go e nmen sa e y measu es a hei business si e. Finally, social dis ancing is he only s ep
ha helps he b oad popula ion o keep away om he co ona i us; hus, a oiding massi e
ga he ings and close con ac s would enable peoples o do hei wo k unde he sa e y
pa ame e s. All o his posi i i y would suppo se ices alue-added on a global scale.
Table 4 shows he ADF uni oo es ima es and ound ha , excep SOCDIS, he emain-
ing a iables exhibi he ﬁ s di e ence s a iona y, while SOCDIS does no show ei he I(0)
o I(1) cha ac e is ics, hus i does no conﬁ m he o de o in eg a ion a he le el o ﬁ s
di e ence. Based on he es ima es, he s udy mo es owa ds quan ile eg ession es ima es
o show he a ia ions o a iables a di e en quan iles dis ibu ion.
156

Heal hca e 2021,9, 220
Table 3. Co ela ion Ma ix.
Va iables SVAD COMD WOM LOCKDOWN FACT EACT PCONT SOCDIS
SVAD 1
—–
COMD −0.925 1
(0.000) —–
WOM 0.912 −0.834 1
(0.000) (0.000) —–
LOCKDOWN
0.726 −0.543 0.821 1
(0.000) (0.000) (0.000) —–
FACT 0.857 −0.809 0.953 0.708 1
(0.000) (0.000) (0.000) (0.000) —–
EACT 0.946 −0.927 0.955 0.703 0.943 1
(0.000) (0.000) (0.000) (0.000) (0.000) —–
PCONT −0.832 0.734 −0.894 −0.716 −0.887 −0.832 1
(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) —–
SOCDIS 0.931 −0.887 0.987 0.772 0.964 0.986 −0.875 1
(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) —–
No e: Small b acke shows p obabili y alue. SVAD shows se ices alue-added, COMD shows communicable disease, WOM shows
wo d-o -mou h, LOCKDOWN shows lockdown, FACT shows ﬁnancial ac i i y, EACT shows economic ac i i y, PCONT shows p ice
con ol, and SOCIDIS shows social dis ancing.
Table 4. Uni Roo Es ima es.
Va iables
Le el Fi s Di e ence
Cons an Cons an wi h T end Cons an Cons an wi h T end
SVAD −0.062
(0.947)
−2.152
(0.503)
−5.892
(0.000)
−5.879
(0.000)
COMD −0.264
(0.921)
−2.196
(0.479)
−6.178
(0.000)
−6.741
(0.000)
WOM −1.542
(0.503)
−0.631
(0.971)
−4.663
(0.000)
−4.922
(0.001)
LOCKDOWN −1.617
(0.465)
−2.073
(0.545)
−7.663
(0.000)
−7.579
(0.000)
FACT −0.386
(0.902)
−2.016
(0.576)
−5.932
(0.000)
−5.859
(0.000)
EACT 1.214(0.997) −1.332
(0.866)
−5.028
(0.000)
−5.255
(0.000)
PCONT −1.757
(0.396)
−3.107
(0.117)
−7.776
(0.000)
−7.718
(0.000)
SOCDIS −0.972
(0.754)
−0.930
(0.943)
−0.730
(0.828)
−0.147
(0.992)
No e: small b acke shows p obabili y alues. SVAD shows se ices alue-added, COMD shows communicable disease, WOM shows
wo d-o -mou h, LOCKDOWN shows lockdown, FACT shows ﬁnancial ac i i y, EACT shows economic ac i i y, PCONT shows p ice
con ol, and SOCIDIS shows social dis ancing.
Table 5 shows he quan ile eg ession es ima es and ound ha communicable diseases
hu he se ices alue added a di e en quan iles dis ibu ion wi h a minimum impac
o
−
0.068% and maximum impac o
−
0312%, while an inc easing one pe cen inc ease
in se ices alue-added sha e o he globe GDP. The esul s a e in e p e ed in ligh o he
no el co ona i us. Kim e al. [
28
] a gued ha communi y heal h is mainly inﬂuenced by
he co ona i us ou b eak ha has inc eased he heal hca e bu den in na ional heal hca e
157
Heal hca e 2021,9, 220
bills. The case s udy o New Yo k ci y de eloped some p o ocols o he ou pa ien se ice
depa men o minimize he isk o co ona i us pandemic, including a ﬁ s s age, he pos-
sible es o co ona i us is pe o med on he suscep ible pa ien s. I ound o be posi i e,
hen he second s ep is o gi e symp oma ic ea men s. The hi d s age is o ack he
pa ien s once du ing a leas ﬁ e consecu i e days, and, ﬁnally, each hem how o isola e
in-home o elsewhe e unde p esc ibed medical guidelines. Sama a hunga [
29
] discussed
he possible challenges o he co ona i us pandemic on in e na ional ou ism in S i Lanka.
The esul s show ha he co ona i us pandemic nega i ely a ec s he coun y’s ou ism
sec o , as i ad e sely a ec s he sou ce ma ke s, local ou ism esou ces, and a el indus y.
The suspension o anspo a ion modes, pa ial and comple e lockdowns, and main aining
he dis ance be ween humans all decline ou ism income. Howe e , hese measu es a e
essen ial in con aining co ona i us in a coun y. Yang e al. [
30
] concluded ha , due o
he high heal h isk o co ona i us pandemics o he na ional and in e na ional ou is s,
he ou ism demand dec eases h ough go e nmen ins i u e bans on human mobili y.
Fu he , a el es ic ions ha a e imposed by he go e nmen exace ba e ad e se ou -
comes om he ou ism sec o . Thus, social wel a e is he subjec ma e and p ime
esponsibili y o he go e nmen . Any s ic policies ega ding hei p e en ion a e desi -
able. Howe e , he go e nmen s should subsidize he ou ism sec o o imp o e ou ism
si es; once he pandemic anishes, an eno mous amoun o ou ism e enue could be gen-
e a ed. Wanjala [
31
] a gued ha no el co ona i us nega i ely a ec s a coun y’s economic
g ow h ia low in e na ional ade and ou ism ansmission mechanisms. The a el and
anspo a ion es ic ions o possible cau ion o ake ca e o he humans om co ona i us
a e desi able, being subs i u ed by he speciﬁc go e nmen -ini ia ed e o ms packages o
he ou ism and ade o main ain economic ac i i ies coun ywide.
Table 5. Quan ile Reg ession Es ima es.
Quan iles τ10 τ20 τ30 τ40 τ50 τ60 τ70 τ80 τ90
LOG(COMD) −0.310 −0.313 −0.283 −0.262 −0.115 −0.105 −0.084 −0.068 −0.162
(0) (0) (0) (0.012) (0.008) (0.026) (0.064) (0.158) (0.017)
LOG(WOM) 0.699 0.860 0.711 0.750 0.327 0.243 0.170 0.201 0.343
(0.001) (0.001) (0.006) (0.022) (0.605) (0.705) (0.794) (0.777) (0.704)
LOG(LOCKDOWN)
0.027 0.010 0.043 0.056 0.247 0.239 0.231 0.208 0.243
(0.484) (0.823) (0.470) (0.472) (0.011) (0.028) (0.051) (0.114) (0.137)
LOG(FACT) −0.112 −0.138 −0.127 −0.129 −0.072 −0.097 −0.122 −0.155 −0.118
(0) (0) (0.001) (0.008) (0.350) (0.289) (0.234) (0.201) (0.405)
LOG(EACT) 0.220 0.178 0.165 0.222 0.418 0.392 0.397 0.420 0.261
(0.026) (0.118) (0.208) (0.181) (0.031) (0.037) (0.027) (0.030) (0.218)
LOG(PCONT) −0.027 −0.029 −0.032 −0.032 −0.030 −0.030 −0.026 −0.027 −0.022
(0.002) (0.008) (0.010) (0.037) (0.009) (0.005) (0.017) (0.023) (0.171)
LOG(SOCDIS) −0.442 −0.451 −0.374 −0.439 −0.447 −0.346 −0.252 −0.239 −0.256
(0.008) (0.018) (0.062) (0.083) (0.282) (0.354) (0.480) (0.518) (0.557)
Cons an 1.834 1.959 1.741 1.020 −2.875 −2.435 −2.343 −2.239 −1.839
(0.170) (0.212) (0.366) (0.678) (0.071) (0.076) (0.034) (0.041) (0.100)
S a is ical Tes s
Slope Equali y
Tes Wald Tes χ2–s a is ic: 37.055 χ2–s a is ic deg ee o
eedom = 14 P obabili y alue: 0.000
Symme ic
Quan iles Tes Wald Tes χ2–s a is ic: 13.616 χ2–s a is ic deg ee o
eedom = 8 P obabili y alue: 0.092
No e: Small b acke shows p obabili y alue. SVAD shows se ices alue-added, COMD shows communicable disease, WOM shows
wo d-o -mou h, LOCKDOWN shows lockdown, FACT shows ﬁnancial ac i i y, EACT shows economic ac i i y, PCONT shows p ice
con ol, and SOCIDIS shows social dis ancing.
158
Heal hca e 2021,9, 220
The sound ﬁnancial ac i i ies, p ice con ol measu es, and social dis ancing ha e
p o en o be he bes s a egy o con ol co ona i us; howe e , hese measu es nega i ely
impac se ices alue-added, leading o a global dep ession. The posi i e impac o wo d-
o -mou h, lockdown, and sound economic ac i i ies dec eases he isk o co ona i us
pandemic and suppo s he se ices sha e in o he wo ld GDP. These esul s ha e been
shown a di e en quan iles dis ibu ion. B odeu e al. [
32
] discussed he ulne abili y
o he COVID-19 pandemic a a mass scale ac oss he globe. The go e nmen pu many
e o s o es ain co ona i us h ough mul iple s a egies. Howe e , he uniﬁed adop ed
policy included lockdown, which bea s mul i ace ed men al heal h challenges o pop-
ula ion well-being ha a e no limi ed o bo edom, loneliness, sadness, wo y, suicidal
hough s, s ess, and di o ce. The need o sma lockdowns and in o ma ion sha ing
among he masses o s ay sa e in homes would be desi able, while he go e nmen should
engage hei popula ion in some online g oup asks o educe men al heal h challenges.
Wong [
33
] desc ibed he eal si ua ion o he co ona i us pandemic in he Malaysian
con ex , whe e he physical dis ancing along wi h he na ional lockdowns we e en o ced
wi h he one o de command ha local popula ion om in e na ional a els, no allow-
ing o eigne s o isi a coun y, empo a y shu down o businesses, closu e o schools,
colleges, and o he ins i u ions. A he same ime, only essen ial se ices ha e been pe -
mi ed unde sa e y measu es. These measu es a ec indus ies, including he se ices
indus y, which may cause a global dep ession. Ba o e al. [
34
] ound ha he co ona i us
pandemic and Spanish ﬂu inc ease mo ali y and economic con ac ion, mos ly low eal
e u ns on s ocks and sho - e m go e nmen bills. Gómez-Ríos e al. [
35
] concluded ha
he co ona i us pandemic was mainly ou o con ol due o he impo ed numbe o cases
om uncon olled ai a elle s. Social dis ancing a oids massi e ga he ings and es ic s
in e na ional a elling o main ain he dec easing end in he in ec ions end. Yezli and
Khan [
36
] a gued ha , besides he socio-economic, poli ical, and eligious challenges aced
by he Kingdom o Saudi A abia, he coun y ook bold s eps o es ain co ona i us
h ough social dis ancing and comple e lockdown. The coun y suddenly closed due o he
high epidemic cu e because o i s social and eligious no ms hos ing massi e eligious
ga he ings. These measu es a e essen ial in con aining he i us, al hough a he cos o
a se e e economic c isis. The se ices indus y mainly su e s due o es ic ions being
imposed on he a el and ou ism sec o , businesses shu down, closu e o educa ional
and o he ins i u ions, and main aining social dis ancing; all o hese measu es would help
o es ain he coun y’s epidemic cu e. Figu e 2 shows he quan ile p ocess es ima es o
eady e e ence.
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Figu e 2.
Quan ile P ocess Es ima es. Sou ce: Au ho s’ es ima es. No e: SVAD shows se ices alue-added, COMD shows communi-
cable disease, WOM shows wo d-o -mou h, LOCKDOWN shows lockdown, FACT shows ﬁnancial ac i i y, EACT shows economic
ac i i y, PCONT shows p ice con ol, and SOCIDIS shows social dis ancing. LOG shows na u al loga i hm. C shows cons an . Red lines
shows he c i ical egion.Blue line shows he es ima ed alue.
4. Discussion
Table 6 shows he endogenei y es esul s ha we e pe o med h ough quan ile median
eg ession. Financial de elopmen gene ally wo ks as a g ow h p oxy; hus, e alua ing he
possible endogenei y in he gi en model, he s udy pe o ms he h ee-s ep p ocedu e.
The ﬁ s s ep is o use ln (FACT) as a dependen a iable ha is eplaced by ln (SVAD),
while he emaining a iables a e exogenous a iables and ob ained i s esidual alue
(i.e. es_01). In he second s ep, ln (SVAD) is used again as a p ima y endogenous a iable,
while es_01 and o he a iables, excep o ln (FACT), a e used as eg esso s and ob ain
coe ﬁcien es ima es. In he ﬁnal s ep, he Wald coe ﬁcien es ic ions a e applied on he
gi en es_01 e m and ound he s a is ically insigniﬁcan esul s o -s a is ics, F-s a is ics,
and Chi-squa e s a is ics. The esul s conﬁ med ha he e a e no possible endogenei y
issues in he quan ile eg ession es ima es. Thus, he esul s a e alid and eliable.
Table 6. Endogenei y Tes pe o med by Quan iles Median Reg ession.
Va iables Fi s S ep: ln (SVAD) Second S ep: ln (FACT) Final S ep: ln (SVAD)
Coe ﬁcien S d. E o -S a is ic P ob. Coe ﬁcien S d. E o -S a is ic P ob. Coe ﬁcien S d. E o -S a is ic P ob.
C−2.875 1.550 −1.854 0.071 6.848 4.894 1.399 0.169 −3.374 1.741 −1.937 0.064
ln(FACT) −0.072 0.077 −0.946 0.350 N/A N/A N/A N/A N/A N/A N/A N/A
ln(COMD) −0.115 0.041 −2.789 0.008 0.434 0.175 2.469 0.018 −0.146 0.030 −4.818 0.000
ln(WOM) 0.327 0.628 0.520 0.605 −1.080 1.638 −0.659 0.513 0.406 0.679 0.598 0.553
ln(lockdown) 0.247 0.092 2.674 0.011 −0.355 0.218 −1.627 0.112 0.273 0.072 3.764 0.000
ln(EACT) 0.418 0.186 2.240 0.031 −0.005 0.538 −0.011 0.991 0.419 0.187 2.240 0.031
ln(PCONT) −0.030 0.011 −2.717 0.009 −0.078 0.032 −2.427 0.020 −0.024 0.009 −2.477 0.017
ln(SOCDIS) −0.447 0.410 −1.090 0.287 1.880 1.118 1.681 0.100 −0.584 0.480 −1.217 0.231
Res_01 N/A N/A N/A N/A N/A N/A N/A N/A −0.072 0.077 −0.946 0.350
Adjus ed R20.852 0.779 0.852
S.E. o
eg ession 0.018 0.044 0.018
Quan ile
dependen
a iable 4.080 4.537 4.080
Spa si y 0.023 0.119 0.023
Wald Coe ﬁcien Res ic ions
Wald Tes -s a is ic: −0.946, p> 0.090 F-s a is ics: 0.896, p> 0.090 Chi-squa e s a is ic: 0.895, p> 0.090
No e: SVAD shows se ices alue-added, COMD shows communicable disease, WOM shows wo d-o -mou h, LOCKDOWN shows
lockdown, FACT shows ﬁnancial ac i i y, EACT shows economic ac i i y, PCONT shows p ice con ol, es_01 shows esidual e m,
and SOCIDIS shows social dis ancing. N/A shows no applicable.
Table 7 shows he IRF es ima es and sugges ed ha sma lockdown se ices will posi-
i ely inﬂuence se ices alue-added, sound ﬁnancial and economic ac i i ies, p ice con ol,
and social dis ancing. In con as , wo d-o -mou h and communicable diseases la gely in-
160

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