Dashboard COMPRIME_COMPRI_MOv: multiscalar spatio-temporal monitoring of the COVID-19 pandemic in Portugal

u u e in e ne A icle Dashboa d COMPRIME_COMPRI_MO : Mul iscala Spa io-Tempo al Moni o ing o he COVID-19 Pandemic in Po ugal Nuno Ma ques da Cos a , Nelson Mileu * and And éAl es   Ci a ion: Ma ques da Cos a, N.; Mileu, N.; Al es, A. Dashboa d COMPRIME_COMPRI_MO : Mul iscala Spa io-Tempo al Moni o ing o he COVID-19 Pandemic in Po ugal. Fu u e In e ne 2021,13, 45. h ps://doi.o g/ 10.3390/ i13020045 Academic Edi o s: Ca los Filipe Da Sil a Po ela and And ew C ooks Recei ed: 17 Janua y 2021 Accep ed: 9 Feb ua y 2021 Published: 12 Feb ua y 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 il- 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/). Ins i u e o Geog aphy and Spa ial Planning, Uni e sidade de Lisboa, 1600-276 Lisbon, Po ugal; [email p o ec ed] (N.M.d.C.); [email p o ec ed] (A.A.) *Co espondence: [email p o ec ed]; Tel.: +351-21-044-30-00 Abs ac : Due o i s no el y, he ecen pandemic o he co ona i us disease (COVID-19), which is associa ed wi h he sp ead o he new se e e acu e espi a o y synd ome co ona i us (SARS-CoV-2), igge ed he public’s in e es in accessing in o ma ion, demons a ing he impo ance o ob aining and analyzing c edible and upda ed in o ma ion om an epidemiological su eillance con ex . Fo his pu pose, heal h au ho i ies, in e na ional o ganiza ions, and uni e si y ins i u ions ha e pub- lished online a ious g aphic and ca og aphic ep esen a ions o he e olu ion o he pandemic wi h daily upda es ha allow he almos eal- ime moni o ing o he e olu iona y beha io o he sp ead, le hali y, and e i o ial dis ibu ion o he disease. The pu pose o his a icle is o desc ibe he echni- cal solu ion and he main esul s associa ed wi h he publica ion o he COMPRIME_COMPRI_MO dashboa d o he dissemina ion o in o ma ion and mul i-scale knowledge o COVID-19. Unde wo apidly implemen ing esea ch p ojec s o inno a i e solu ions o espond o he COVID-19 pandemic, p omo ed in Po ugal by he FCT (Founda ion o Science and Technology), a websi e was c ea ed. Tha websi e b ings oge he a di e se se o a iables and indica o s in a dynamic and in e ac i e way ha e lec s he e olu iona y beha io o he pandemic om a mul i-scale pe spec i e, in Po ugal, cons i u ing i sel as a sys em o moni o ing he e olu ion o he pandemic. In he cu en si ua ion, his ype o explo a o y solu ions p o es o be c ucial o gua an ee e e yone’s access o in o ma ion while simul aneously eme ging as an epidemiological su eillance ool ha is capable o assis ing decision-making by public au ho i ies wi h compe ence in de ining con ol policies and igh he sp ead o he new co ona i us. Keywo ds: dashboa d; WebGIS; da a analy ics; COVID-19; SARS-CoV-2 1. In oduc ion In Decembe 2019, se e al cases o pneumonia o unknown o igin appea ed in China. Ea lie ha yea , he Wo ld Heal h O ganiza ion (WHO) had published a lis o en majo global h ea s, including pandemics associa ed wi h espi a o y diseases [ 1 ]. La e , in Janua y 2020, a new se e e acu e espi a o y synd ome co ona i us (SARS-CoV-2) was iden i ied and ecognized as esponsible o he sp ead o he COVID-19 disease. The i s eco ds o in ec ion by SARS-CoV-2, ini ially ci cumsc ibed in he Chinese e i o y, quickly sp ead, wi h a p og essi e inc ease in he numbe o in ec ed by he new co ona i us and i s sp ead o dozens o coun ies. Due o he apid p og ession o he disease, he inc ease in he numbe o dea hs associa ed wi h i , and i s widesp ead expansion, he WHO decla ed COVID-19 as a pandemic on 11 Ma ch 2020. By his da e, mo e han 100,000 people we e in ec ed in 114 coun ies, and he numbe o dea hs was al eady 4000 [ 2 ]. Nine mon hs la e , he numbe o con i med cases in he wo ld has exceeded 60 million, and he numbe o dea hs is o e 1.5 million [3], a es ing o he high ansmissibili y o he disease. Fu u e In e ne 2021,13, 45. h ps://doi.o g/10.3390/ i13020045 h ps://www.mdpi.com/jou nal/ u u ein e ne Fu u e In e ne 2021,13, 45 2 o 17 Al eady in a pandemic si ua ion, he WHO eques ed se e al coun ies wi h cases o in ec ion o main ain an open policy o communica ion and dissemina ion o in o ma ion abou he si ua ion in hei coun ies. This eques esul ed om he ac ha du ing he las SARS epidemic (se e e acu e espi a o y synd ome), an eme ging disease caused om in ec ion by he SARS co ona i us, in 2003, he lack o anspa en and upda ed disclosu e o he numbe o cases made i di icul o con ol and manage he epidemic, hus e idencing ha “ anspa ency is he bes policy” [ 4 ]. Following his eques , he WHO i sel se an example by p o iding a dashboa d ha ga he s a se o da a on he e olu ion o he pandemic si ua ion in he wo ld [3]. In his amewo k, heal h au ho i ies in he a ious a ec ed coun ies ha e communi- ca ed he e olu ion o he pandemic si ua ion by making da a a ailable o he public. A his junc u e, also he public in e es o access o in o ma ion has been high, as shown by he s udy REACT COVID—Su ey on Food and Physical Ac i i y in he Con ex o Social Con en ion [ 5 ], whe e i was ound ha almos 80% o esponden s in Po ugal seek in o ma ion on heal h ca e and mo e han 94% ha e accessed in o ma ion on COVID-19. Howe e , abou 56% s a e ha hey ha e di icul y unde s anding i . This las inding is an indica ion o he need o de elop simple ep esen a ions capable o ansmi ing in o ma ion on he pandemic si ua ion o he popula ion wi h di e en le els o heal h li e acy. The use o explo a o y da a me hods, such as dashboa ds applied o moni o ing he co ona i us pandemic, has been de eloped by se e al au ho s, o hei e sa ili y, speed o analysis, and ease o unde s anding by decision make s and he gene al public. Fo Boulos and Ge agh y, dashboa ds became an essen ial sou ce o in o ma ion du ing he COVID-19 ou b eak, con ibu ing o he p o ec ion and educ ion o i s ha m ul e ec s [ 6 ]. The main objec i e o his a icle is o p esen he dashboa d COMPRIME_COMPRI_MO echnical solu ion and da a analy ics esul s o moni o ing he e olu ion o he COVID-19 disease si ua ion in Po ugal. The dashboa d was published online in o de o be a means o dissemina ion o mul i-scale in o ma ion and knowledge bu also a suppo o analysis o he main ime ends and e i o ial pa e ns o SARS-CoV-2 con agion in Po ugal, and i allows access o mul iple indica o s and in e ac i e explo a ion o g aphics and dynamic maps. The esea ch pa h was based on he in o ma ion collec ed om he p ojec ’s s akeholde s, namely he dashboa d pu pose, dashboa d use s, unc ional unc ionali ies, design ea u es, and how i could suppo he decision p ocess. The de elopmen o he dashboa d was associa ed wi h wo esea ch p ojec s, bo h o hem apid implemen a ion p ojec s o inno a i e solu ions in esponse o he pan- demic o COVID 19 unde he excep ional unding line “RESEARCH 4 COVID-19” o he FCT (Po uguese Founda ion o Science and Technology) (h ps://www. c .p /apoios/ esea ch4co id19/edicao_1/index.ph ml.p ) (accessed on 9 Feb ua y 2021), which aims o suppo esea ch and de elopmen p ojec s and ini ia i es ha mee he needs o he Na ional Heal h Se ice: 1. COMPRIME—COnhece Mais PaRa In e i MElho (Ge o Know Mo e o In e en ion) —has as i s main objec i e o iden i y he p opaga ion dynamics o SARS-CoV-2, in i s ela ions wi h he demog aphic and socioeconomic p o iles o he e i o ies, a he municipali y scale, iden i ying he de e mining ac o s o his p opaga ion; 2. COMPRI_MO —COnhece Mais PaRa In e i melho no con ex o da Mobilidade (Ge o Know Mo e o In e en ion in he con ex o mobili y)—aims o cha ac e ize he mobili y o popula ions gi en he in ensi y, mo i a ion, and geog aphical pa e n o he lows and, associa ing hese dynamics wi h epidemiological da a, assess he isk o p opaga ion associa ed wi h mobili y. The p ojec in ends o p opose a moni o ing sys em o suppo he decision and p esen he basis o a model o he simula ion o p opaga ion based on mobili y. Thus, wi hin hese p ojec s, we de eloped he dashboa d, which is s uc u ed in ou componen s co esponding o he scales o analysis: in e na ional, na ional, e- gional, and municipal. The dashboa d is published online a he ollowing add ess: h ps://www.comp ime-comp i-mo .com/dashboa ds.h ml (accessed on 9 Feb ua y 2021), Fu u e In e ne 2021,13, 45 3 o 17 wi h an English e sion a he ollowing add ess: h ps://www.comp ime-comp i-mo . com/dashboa dsenglish.h ml (accessed on 9 Feb ua y 2021). The in o ma ion used in he dashboa d is me ely an e olu iona y ollow-up based on o icial in o ma ion om he Di- ec o a e Gene al o Heal h [ 7 ] in he o m o daily epidemiological epo s, based on which se e al me ics we e calcula ed. Thus, he COMPRIME_COMPRI_MO dashboa d does no include any ou pu o conclusions ob ained in he scope o he p ojec s o in o ma ion o p edic i e cha ac e , being i s unc ion o ep esen he e olu ion o he epidemiological si ua ion based on o icial in o ma ion. This a icle is o ganized in six pa s. The i s co esponds o his in oduc ion, which is ollowed by a b ie con ex ualiza ion o he impo ance and con ibu ions o using dashboa ds o he s udy o COVID-19. The hi d pa conce ns he me hodologies used, di iding i sel be ween he backg ound, a chi ec u e, and he da a. The ollowing shows he echnical solu ion designed and b ie ly desc ibes he main p ocesses and ends o p opaga ion o COVID-19 in Po ugal, making i possible o wi hd aw om he dashboa d. In he i h pa , he esul s achie ed wi h he dashboa d a e discussed, and in he las pa , he conclusions a e p esen ed. 2. Use o Dashboa ds in he Con ex o he Pandemic The use o spa ial analysis in acking and unde s anding he sp ead o in ec ious diseases using ca og aphy is an old p ocess. One o he mos widesp ead examples o analysis in he li e a u e is he map o physician John Snow, who in he nine een h cen u y iden i ied he o igin o an ou b eak o chole a h ough he spa ial ela ionships be ween he occu ences o dea hs by disease and he loca ion o wa e wells in he ci y o Lon- don [ 8 ]. Wi h he de elopmen o Geog aphic In o ma ion Sys ems (GIS), he possibili ies o analyzing, isualizing, and de ec ing disease pa e ns ha e inc eased signi ican ly, as p o ed by he g owing numbe o publica ions [ 9 ]. Using examples a di e en scales, Zhou e al. analyzed he con ibu ion o GIS and big da a in comba ing he pandemic, wi h he isualiza ion o in o ma ion cons i u ing one o he challenges in he esponse o he pandemic [ 10 ]. In addi ion, F anch-Pa do e al. p esen se e al s udies using spa ial analy- sis and o he GIS echniques o s udy he geog aphical dimension o COVID-19, some o which he au ho s add in he ca ego y o web-based mapping as hey a e ca og aphic ep- esen a ions o he pandemic si ua ion a ailable online [ 11 ]. In he con ex o a pandemic, he o ms o ep esen a ion o he disease si ua ion ha e mul iplied, wi h dashboa ds being he p edominan solu ion. As Sa o and Ka uppannan poin ou , making da a a ailable on in e ac i e dashboa ds in eal ime, o nea eal ime, has become a use ul ool by which many coun ies p esen speci ic in o ma ion on COVID-19 [ 12 ]. In his sense, Boulos and Ge agh y p esen se e al examples o WebGIS and dashboa ds o ack he sp ead o he new co ona i us wi h he aim o discussing addi ional ways hese ools con ibu e o com- ba ing ou b eaks o in ec ious diseases and epidemics [ 6 ]. This ype o solu ion is c ucial by acili a ing anspa en access o in o ma ion o he en i e popula ion in a simple way, ensu ing he moni o ing o he si ua ion e olu ion om an epidemiological su eillance poin o iew, no only ega ding he numbe o new in ec ions bu also o he pa ame e s and a a ious scales, also allowing he heal h au ho i ies a igo ous moni o ing. WHO and Johns Hopkins Uni e si y we e pionee s in ep esen ing he pandemic si ua ion in a ious g aphic and ca og aphic ways, wi h he Cen e o Sys ems Science and Enginee ing (CSSE) dashboa d a Johns Hopkins Uni e si y [ 13 ] being used as an o icial sou ce o in e na ional in o ma ion. O he examples could be gi en, and he e a e e en published s udies by esea che s such as Fe nandez-Lozano and Ced on [ 14 ] ha ha e de eloped an in e ac i e and dynamic dashboa d o moni o ing COVID-19 o suppo he epidemi- ological s udy o he disease in Spain, o Ba one e al. [ 15 ], who p opose a se o ways o explo e and analyze epidemiological da a o COVID-19 om a spa io- empo al pe spec i e wi h explo a i e and non-in e en ial me ics. Wi hou neglec ing he impo ance ha hese solu ions ha e o epidemiological moni o ing and su eillance, i is c ucial o add ess o he s ha add a p edic i e componen o he e olu ion and ha na u ally ha e a g ea e Fu u e In e ne 2021,13, 45 4 o 17 weigh in helping make decisions ega ding he con ol o con agions. In his sense, Flo ez and Singh [ 16 ] combine in e na ional moni o ing o he e olu ion o he numbe o cases and dea hs associa ed wi h COVID-19 wi h he p edic ion o he e olu ion o hese indica- o s using quad a ic equa ions. Despi e he simple p ojec ion using pu ely ma hema ical models, igno ing o he a iables and geog aphical di e en ia ions o he phenomenon di usion wi h impo ance o a mo e igo ous es ima ion, his is s ill a posi i e con ibu ion owa d he analysis and e alua ion o isk o u u e in ec ion. In he Eu opean con ex , he Eu opean Cen e o Disease Con ol and P e en ion (ECDC) has de eloped i s own solu ion o moni o ing de elopmen s [ 17 ] in he Eu opean Union and he Eu opean Economic A ea, by coun ies and egions, while main aining he in e na ional si ua ion moni o ing. In Po ugal, he na ional heal h au ho i y o icial online se ice is he DGS (Di eção- Ge al da Saúde – Di ec o a e-Gene al o Heal h) in e ac i e pla o m [ 18 ]. This pla o m ep oduces he o icial epo s published daily [ 7 ] a na ional, egional, and municipal le el (weekly), bu no o he me ics and indica o s a e a ailable wi h he o icial in o ma ion. The Na ional Ins i u e o S a is ics (INE) has also designed a solu ion o he same kind, wi h special ocus on municipali ies and whe e i makes a ailable, o each analysis uni , s a is ical a iables, and indica o s om i s da abase in an a emp o complemen he eading o he epidemiological si ua ion [19]. The “COVID-19 Insigh ” pla o m [ 20 ] is one o he mos comple e p oposals o mul i-scale and mul i- hema ic epidemiological moni o ing which, in addi ion o including a municipal isk index, allows moni o ing and o ecas ing he impac s on he economy and changes in mobili y, as well as epidemiological es ima ion models o a ious ele an indica o s. Finally, and wi h he same ype o a chi ec u e as he DGS and INE solu ions, he Po uguese Associa ion o Geog aphe s (APG) pa ially eplica es he mos ele an na- ional in o ma ion by moni o ing in g ea e de ail he e olu ion o cases pe municipali y, p o iding he absolu e a ia ion in he numbe o new cases and he accumula ed pe inhabi an [21]. 3. Ma e ials and Me hods 3.1. Backg ound The ans o ma ion o la ge olumes o da a in o in o ma ion using dashboa ds is a p ac ice in se e al domains. F om he ypical dashboa ds associa ed wi h managemen [ 22 ], h ough i s adop ion in he con ex o sma ci ies [ 23 , 24 ] o in heal h [ 25 ], se e al examples can be ound in he li e a u e. Al hough he e a e se e al dashboa d de ini ions [ 23 , 24 ], hey all sha e he ac ha i cons i u es a communica ion mechanism o suppo decision making. In his a icle, he de ini ion o Yigi basioglu and Velcu was adop ed, whe e a “dashboa d can be ega ded as a da a-d i en decision suppo sys em, which p o ides in o ma ion in he pa icula o ma o he decision make ” [ 22 ]. Ano he impo an aspec in he cons uc ion o a dashboa d, is ela ed o he ype o use. In his espec , S ephen Few’s In o ma ion Dashboa d Design [ 26 ] es ablishes a use ul axonomy, p oposing h ee ca ego ies: s a egic, ope a ional, and analy ical. Taking in o accoun he objec i es asso- cia ed wi h he esea ch p ojec , i was conside ed ha he COMPRIME_COMPRI_MO dashboa d i in o he ope a ional ypology [ 27 ], p o iding desc ip i e measu emen s using indica o s based on o iginal da a and o he ela ed da a, in o de o p o ide mul i- empo al and mul i-scale in o ma ion. The esea ch me hodology was adap ed om Yigi basioglu and Velcu [ 22 ], o ganizing in he ollowing concep ual ela ionships: pu pose, use s, design ea u es, and decision- making (Figu e 1). The implemen a ion o concep s and ela ionships be ween en i ies was based on discussion and analysis among he s akeholde s in ol ed in he p ojec . Fi s ly, he en i ies in ol ed es ablished he main objec i e o he dashboa d o moni o cases o in ec ion and o calcula e indica o s using auxilia y in o ma ion o allow unde s and- ing/explaining he sp ead o he i us in he e i o y. The i s s ep was he assembly o Fu u e In e ne 2021,13, 45 5 o 17 app op ia e ime se ies da a and geog aphic in o ma ion. Based on he numbe o cases and auxilia y demog aphic in o ma ion, he indica o s ha make up he dashboa d a e calcula ed. The calcula ion o indica o s (e.g., con i med cases pe 10,000 inhabi an s by municipali y, isk classi ica ion) allows es ablishing he ela ionship be ween he pandemic si ua ion and he socio-economic con ex . Fu u e In e ne 2021, 13, x FOR PEER REVIEW 5 o 19 The esea ch me hodology was adap ed om Yigi basioglu and Velcu [22], o gan- izing in he ollowing concep ual ela ionships: pu pose, use s, design ea u es, and de- cision-making (Figu e 1). The implemen a ion o concep s and ela ionships be ween en- i ies was based on discussion and analysis among he s akeholde s in ol ed in he p o- jec . Fi s ly, he en i ies in ol ed es ablished he main objec i e o he dashboa d o moni o cases o in ec ion and o calcula e indica o s using auxilia y in o ma ion o allow unde s anding/explaining he sp ead o he i us in he e i o y. The i s s ep was he assembly o app op ia e ime se ies da a and geog aphic in o ma ion. Based on he numbe o cases and auxilia y demog aphic in o ma ion, he indica o s ha make up he dashboa d a e calcula ed. The calcula ion o indica o s (e.g., con i med cases pe 10,000 inhabi an s by municipali y, isk classi ica ion) allows es ablishing he ela ionship be- ween he pandemic si ua ion and he socio-economic con ex . Figu e 1. Dashboa d esea ch pa hs. The unc ional ea u es iden i ied by he p ojec ’s s akeholde s we e he isualiza- ion o in o ma ion h ough maps, he use o simple and dynamic g aphics, and he is- ualiza ion o he big s a is ical numbe s associa ed wi h he numbe o cases. The p inci- ples o isualizing da a iden i ied by he p ojec s akeholde s we e he isualiza ion on a one-page s yle and d illdown s yle con aining all he maps and g aphs (Figu e 2). The sc een is o ganized by geog aphic scales, and each le el includes elemen s such as maps, g aphs, and indica o s. Based on he equi emen s de ined by he s akeholde s and he pu pose o he dashboa d, he in eg a ion o he map and o he elemen s assumed he map as pa o he G aphic Use In e ace (GUI) [23]. The in e ac i e spa io- empo al ex- plo a ion, and spa io- empo al in o ma ion decoding cons i u es he suppo o deci- sion-making. In o de o p o ide an in e ac i e explo a ion o spa io empo al da a, he ime slid- e s we e de eloped o make a web maps depic ing ime se ies in o ma ion using p o- po ional symbols [28] and cho ople h maps. Figu e 1. Dashboa d esea ch pa hs. The unc ional ea u es iden i ied by he p ojec ’s s akeholde s we e he isualiza ion o in o ma ion h ough maps, he use o simple and dynamic g aphics, and he isualiza ion o he big s a is ical numbe s associa ed wi h he numbe o cases. The p inciples o isualizing da a iden i ied by he p ojec s akeholde s we e he isualiza ion on a one-page s yle and d illdown s yle con aining all he maps and g aphs (Figu e 2). The sc een is o ganized by geog aphic scales, and each le el includes elemen s such as maps, g aphs, and indica o s. Based on he equi emen s de ined by he s akeholde s and he pu pose o he dashboa d, he in eg a ion o he map and o he elemen s assumed he map as pa o he G aphic Use In e ace (GUI) [ 23 ]. The in e ac i e spa io- empo al explo a ion, and spa io- empo al in o ma ion decoding cons i u es he suppo o decision-making. In o de o p o ide an in e ac i e explo a ion o spa io empo al da a, he ime slide s we e de eloped o make a web maps depic ing ime se ies in o ma ion using p opo ional symbols [28] and cho ople h maps. 3.2. A chi ec u e To in eg a e da a and he logic om a ious sys ems and de i e new unc ionali ies, such as mul i- empo al and mul i-scale managemen , a combined app oach based on Es i’s A cGIS Online echnology was chosen (Figu e 3). All exis ing g aphical elemen s, excep ex e nal inco po a ions and ca og aphy, we e de eloped om A cGIS Online dashboa d unc ionali ies. WebGIS ca og aphy was de eloped using he Lea le map lib a y and jQue y unc ion lib a y, in a solu ion ha combines HTML (Hype Tex Ma kup Language), CSS (Cascading S yle Shee s) and JS (Ja aSc ip ), o allowing g ea e de elopmen eedom, in e ac i i y and que y speed. The ca og aphy was de eloped combining he Lea le map lib a y and some o i s plugins such as Lea e .mig a ionLaye ( o iewing impo ed case lows) wi h he jQue y lib a y. Bo h he p opo ional ci cle maps and he cho ople hs p esen in he dashboa d allow he use o se he da e o he da a se ies o be ep esen ed by a ime slide om jQue y. Due o he ex e nal ca og aphic de elopmen , he ca og aphy was published online on a hos ing pla o m and hen inco po a ed in o he dashboa d. Fu u e In e ne 2021,13, 45 6 o 17 Fu u e In e ne 2021, 13, x FOR PEER REVIEW 6 o 19 Figu e 2 - Dashboa d design. Figu e 2. Dashboa d design. Fu u e In e ne 2021,13, 45 7 o 17 Fu u e In e ne 2021, 13, x FOR PEER REVIEW 7 o 19 3.2. A chi ec u e To in eg a e da a and he logic om a ious sys ems and de i e new unc ionali ies, such as mul i- empo al and mul i-scale managemen , a combined app oach based on Es i’s A cGIS Online echnology was chosen (Figu e 3). All exis ing g aphical elemen s, excep ex e nal inco po a ions and ca og aphy, we e de eloped om A cGIS Online dashboa d unc ionali ies. Figu e 3 - Dashboa d a chi ec u e. WebGIS ca og aphy was de eloped using he Lea le map lib a y and jQue y unc ion lib a y, in a solu ion ha combines HTML (Hype Tex Ma kup Language), CSS (Cascading S yle Shee s) and JS (Ja aSc ip ), o allowing g ea e de elopmen eedom, in e ac i i y and que y speed. The ca og aphy was de eloped combining he Lea le map lib a y and some o i s plugins such as Lea e .mig a ionLaye ( o iewing impo ed case lows) wi h he jQue y lib a y. Bo h he p opo ional ci cle maps and he cho o- ple hs p esen in he dashboa d allow he use o se he da e o he da a se ies o be ep esen ed by a ime slide om jQue y. Due o he ex e nal ca og aphic de elopmen , he ca og aphy was published online on a hos ing pla o m and hen inco po a ed in o he dashboa d. 3.3. Da a The da a o he na ional e i o y come om he daily epo s [7] and dashboa d o DGS [18]. Despi e he wo k de eloped by DGS o he daily p epa a ion o epidemio- logical newsle e s and hei a ailabili y o he public, he in o ma ion is made a ailable exclusi ely in Po able Documen Fo ma and dashboa d, i.e., i is no p o ided in a o ma ha could be easily manipula ed and submi ed o analysis and modeling asks o can be in eg a ed in o a GIS, which is a limi a ion o he use o he da a. The e o e, he use o he in o ma ion o analysis asks equi es he manual collec ion o he in o ma ion, subjec o cou se o e o s. I was also necessa y o edi and co ec he se ies when hey ep esen educ ions in he numbe o accumula ed cases due o ecoun s. This edi ion was impe a i e o a p ope ep esen a ion o he g aphic and ca og aphic in o ma ion. Va ious changes ha ha e occu ed in he in o ma ion made a ailable in he daily e- po s should also be no ed. Tha in o ma ion no longe includes impo ed cases, which limi s he knowledge o he geog aphical o igin o new cases associa ed wi h in e na- ional con ac s. I should also be no ed ha his o ical co ec ions in he se ies made by Figu e 3. Dashboa d a chi ec u e. 3.3. Da a The da a o he na ional e i o y come om he daily epo s [ 7 ] and dashboa d o DGS [ 18 ]. Despi e he wo k de eloped by DGS o he daily p epa a ion o epidemiological newsle e s and hei a ailabili y o he public, he in o ma ion is made a ailable exclusi ely in Po able Documen Fo ma and dashboa d, i.e., i is no p o ided in a o ma ha could be easily manipula ed and submi ed o analysis and modeling asks o can be in eg a ed in o a GIS, which is a limi a ion o he use o he da a. The e o e, he use o he in o ma ion o analysis asks equi es he manual collec ion o he in o ma ion, subjec o cou se o e o s. I was also necessa y o edi and co ec he se ies when hey ep esen educ ions in he numbe o accumula ed cases due o ecoun s. This edi ion was impe a i e o a p ope ep esen a ion o he g aphic and ca og aphic in o ma ion. Va ious changes ha ha e occu ed in he in o ma ion made a ailable in he daily epo s should also be no ed. Tha in o ma ion no longe includes impo ed cases, which limi s he knowledge o he geog aphical o igin o new cases associa ed wi h in e na ional con ac s. I should also be no ed ha his o ical co ec ions in he se ies made by DGS some imes occu due o delays in epo ing by labo a o ies o due o inco ec alloca ion o cases o e i o ial uni s, bu he co ec ion p ocess is no made a ailable by DGS. The main consequence is ha he accumula ed numbe s o some a iables do no ma ch wi h he sum o daily alues. Whene e his happens, da a a e upda ed as much as possible om he a ailable in o ma ion. In addi ion, he in o ma ion on a municipal scale is no longe disclosed wi h a ixed pe iodici y, and he disclosu e o accumula ed cases pe municipali y has been discon inued. Now, i p o ides a 14 days he cumula i e incidence pe 100,000 inhabi an s. These changes also cons i u e cons ain s o he main enance and upda e o he in o ma ion p esen in he dashboa ds. The da a on he in e na ional scale a e based on in o ma ion om he WHO dash- boa d [ 3 ] and he po al “Co ona i us Pandemic (COVID-19)”, which compiles a se o da a om he ECDC [ 29 ]. Due o he use o hese wo sou ces o moni o ing he si ua ion a an in e na ional le el, i is some imes possible ha he e is no a comple e ma ching o he quan i ies eco ded by bo h. The in o ma ion ega ding dashboa d cha s and g aphs has been s uc u ed in Excel iles, due o i s ease o impo and daily upda e in A cGIS Online. Rega ding WebGIS ca - og aphy, he in o ma ion is s uc u ed in GeoJSON o ma ha con ains all he associa ed da a se ies, opology, and coo dina es. 4. Resul s This dashboa d ensu es he moni o ing o he e olu ion o COVID-19 a a ious scales, in a close a icula ion be ween he geog aphic and empo al dimensions. The in e ac i i y and dynamism o he a ious g aphic elemen s (Figu e 4a, b) is a gua an ee o ease o consul a ion and access o all a ailable in o ma ion. The p oduc ion o dynamic WebGIS ca og aphy wi h ime con ol ensu es he ep esen a ion o a iables in a spa io- Fu u e In e ne 2021,13, 45 8 o 17 empo al pe spec i e (Figu e 4c– ), p o ing o be o g ea con ibu ion o he in e p e a ion o p ocesses and ends o e olu ion o he phenomenon and i s p opaga ion in space and o e ime. Fu u e In e ne 2021, 13, x FOR PEER REVIEW 8 o 19 DGS some imes occu due o delays in epo ing by labo a o ies o due o inco ec al- loca ion o cases o e i o ial uni s, bu he co ec ion p ocess is no made a ailable by DGS. The main consequence is ha he accumula ed numbe s o some a iables do no ma ch wi h he sum o daily alues. Whene e his happens, da a a e upda ed as much as possible om he a ailable in o ma ion. In addi ion, he in o ma ion on a municipal scale is no longe disclosed wi h a ixed pe iodici y, and he disclosu e o accumula ed cases pe municipali y has been discon inued. Now, i p o ides a 14 days he cumula i e in- cidence pe 100,000 inhabi an s. These changes also cons i u e cons ain s o he main e- nance and upda e o he in o ma ion p esen in he dashboa ds. The da a on he in e na ional scale a e based on in o ma ion om he WHO dash- boa d [3] and he po al “Co ona i us Pandemic (COVID-19)”, which compiles a se o da a om he ECDC [29]. Due o he use o hese wo sou ces o moni o ing he si ua ion a an in e na ional le el, i is some imes possible ha he e is no a comple e ma ching o he quan i ies eco ded by bo h. The in o ma ion ega ding dashboa d cha s and g aphs has been s uc u ed in Ex- cel iles, due o i s ease o impo and daily upda e in A cGIS Online. Rega ding WebGIS ca og aphy, he in o ma ion is s uc u ed in GeoJSON o ma ha con ains all he asso- cia ed da a se ies, opology, and coo dina es. 4. Resul s This dashboa d ensu es he moni o ing o he e olu ion o COVID-19 a a ious scales, in a close a icula ion be ween he geog aphic and empo al dimensions. The in- e ac i i y and dynamism o he a ious g aphic elemen s (Figu e 4a, b) is a gua an ee o ease o consul a ion and access o all a ailable in o ma ion. The p oduc ion o dynamic WebGIS ca og aphy wi h ime con ol ensu es he ep esen a ion o a iables in a spa- io- empo al pe spec i e (Figu es 4c– ), p o ing o be o g ea con ibu ion o he in e - p e a ion o p ocesses and ends o e olu ion o he phenomenon and i s p opaga ion in space and o e ime. Since he publica ion o he dashboa d in Oc obe 2020 un il he mon h o No embe 2020, he e we e abou 600 isi s and 1191 page iews, co esponding o a daily a e age o 10 isi s. (a) (b) Fu u e In e ne 2021, 13, x FOR PEER REVIEW 9 o 19 (c) (d) (e) ( ) Figu e 4 - In e ac i i y o he dashboa d elemen s. Sou ce: h ps://www.comp ime-comp i-mo .com (accessed on 9 Feb- ua y 2021). The dashboa d is s uc u ed in ou componen s, each ep esen ing a di e en scale o analysis (in e na ional, na ional, egional, and municipal). 4.1. In e na ional Scale In moni o ing he si ua ion on an in e na ional scale (Figu e 5), he dashboa d is di- ided in o wo pa s: 1. The le hal ha esul s om he WHO da a collec ion [3] in which he main igu es (con i med cases, dea hs, new cases, new dea hs, and mo ali y a e) and he coun- ies ha egis e a apid inc ease in hem in absolu e e ms and by hei popula ion a e highligh ed. The p opo ions o cases and dea hs in he wo ld con ex a e also ep esen ed o he 10 mos a ec ed coun ies (Figu e 5a, c). 2. The igh hal whe e six ex e nal elemen s a e inco po a ed: daily a ia ion o new con i med cases pe coun y (Figu e 5b), new cases pe million inhabi an s, new dea hs pe million inhabi an s (Figu e 5d), e olu ion o he o al numbe o cases and Figu e 4. In e ac i i y o he dashboa d elemen s. Sou ce: h ps://www.comp ime-comp i-mo .com (accessed on 9 Feb ua y 2021). Since he publica ion o he dashboa d in Oc obe 2020 un il he mon h o No embe 2020, he e we e abou 600 isi s and 1191 page iews, co esponding o a daily a e age o 10 isi s. Fu u e In e ne 2021,13, 45 9 o 17 The dashboa d is s uc u ed in ou componen s, each ep esen ing a di e en scale o analysis (in e na ional, na ional, egional, and municipal). 4.1. In e na ional Scale In moni o ing he si ua ion on an in e na ional scale (Figu e 5), he dashboa d is di ided in o wo pa s: 1. The le hal ha esul s om he WHO da a collec ion [ 3 ] in which he main igu es (con i med cases, dea hs, new cases, new dea hs, and mo ali y a e) and he coun ies ha egis e a apid inc ease in hem in absolu e e ms and by hei popula ion a e highligh ed. The p opo ions o cases and dea hs in he wo ld con ex a e also ep esen ed o he 10 mos a ec ed coun ies (Figu e 5a,c). 2. The igh hal whe e six ex e nal elemen s a e inco po a ed: daily a ia ion o new con i med cases pe coun y (Figu e 5b), new cases pe million inhabi an s, new dea hs pe million inhabi an s (Figu e 5d), e olu ion o he o al numbe o cases and dea hs in he wo ld, e olu ion o accina ion doses adminis e ed and, inally, he WHO dashboa d. Fu u e In e ne 2021, 13, x FOR PEER REVIEW 10 o 19 dea hs in he wo ld, e olu ion o accina ion doses adminis e ed and, inally, he WHO dashboa d. (a) (b) (c) (d) Figu e 5 - Example o dashboa d elemen s o he in e na ional scale. Sou ce: h ps://www.comp ime-comp i-mo .com (accessed on 9 Feb ua y 2021). In he con ex o he in e na ional componen , he op ion o inco po a ing he ex- e nal elemen s men ioned, as opposed o hei collec ion and subsequen edi ing and ep esen a ion, esul s om he slowness o cons an upda ing o he si ua ion o all coun ies wi h incidence o he disease. Mo eo e , he inco po a ion o hese elemen s allows he use o access a as amoun o in o ma ion published in hese sou ces, con- ibu ing o he access o mo e in o ma ion on he phenomenon. 4.2. Na ional Le el As o he na ional con ex , pa icula impo ance is gi en o he la ge numbe s (con i med cases, ac i e, dea hs, eco e ed, and hospi alized) using 11 line g aphs o ep esen he e olu ion o he main a iables made a ailable in he DGS daily bulle ins. Me ics calcula ed om he in o ma ion in he DGS epo s we e also included, such as he a e age o new in ec ions in he las 14 days and he con i med and ac i e cases pe 10,000 inhabi an s. I also includes wo in e ac i e maps (one o lows and one o p o- po ional ci cles), ep esen ing he o igin o impo ed cases (wi h empo al a ia ion), which is accompanied by wo ho izon al ba g aphs exp essing he numbe and ela i e pe cen age o he 10 coun ies o o igin o he mos cases impo ed in o Po ugal, and also Figu e 5. Example o dashboa d elemen s o he in e na ional scale. Sou ce: h ps://www.comp ime-comp i-mo .com (accessed on 9 Feb ua y 2021). In he con ex o he in e na ional componen , he op ion o inco po a ing he ex e nal elemen s men ioned, as opposed o hei collec ion and subsequen edi ing and ep esen a- ion, esul s om he slowness o cons an upda ing o he si ua ion o all coun ies wi h incidence o he disease. Mo eo e , he inco po a ion o hese elemen s allows he use o access a as amoun o in o ma ion published in hese sou ces, con ibu ing o he access o mo e in o ma ion on he phenomenon. Fu u e In e ne 2021,13, 45 16 o 17 The e olu ion o he dashboa d is expec ed o in eg a e p edic i e models suppo ed by mobili y da a, and he limi a ions associa ed wi h eal- ime da a a ailabili y will be o e come h ough he p o ision o webse ices by he na ional heal h au ho i y. 6. Conclusions Geog aphic in o ma ion sys ems in gene al and web echnologies in pa icula a e indispensable ools in he p o ision and sha ing o pandemic in o ma ion in eal ime o unde s and he p ocesses o con agion and suppo decision-making. The dashboa d elabo a ed and p esen ed in his a icle allows moni o ing “almos in eal ime” he e olu- ion o he COVID-19 disease a di e en scales and acco ding o di e en pe spec i es, making a ailable in a dynamic and in e ac i e way he main indica o s and a iables ha syn hesize he pandemic si ua ion om an explo a o y and no in e en ial poin o iew. The possibili y o combining he ca og aphic ep esen a ion o a ious indica o s wi h hei empo al di e en ia ion allows a clea unde s anding o he dynamics and p ocesses o i us sp ead h oughou he na ional e i o y a egional and municipal scales. This is he main ad an age o he solu ion de eloped compa ed o simila ones, and i is possible o consul in o ma ion ega ding se e al indica o s o all he da es when o icial da a a e a ailable. Al hough he exis ing knowledge abou he sp ead o he disease is no ye su icien o con ol i , he ools o su eillance and epidemiological con ol, such as dashboa ds, con inue o ha e an added impo ance in moni o ing in ec ions om a spa io- empo al pe spec i e. The a ailabili y o his ype o pla o m, which is an agg ega o o o icial in o ma ion p o iding i in an accessible, in e ac i e, and anspa en way, con ibu es o ampli ying he dissemina ion o knowledge, p o iding impo an insigh s on he sp ead in space and ime o he disease, suppo ing he popula ion and o he en i ies wi h de ailed in o ma ion so hey can make as in o med decisions as possible. Au ho Con ibu ions: P ojec adminis a ion, N.M.d.C.; unding acquisi ion, N.M.d.C.; supe ision, N.M.d.C.; o mal analysis N.M.d.C.; w i ing— e iew and edi ing, N.M.d.C.; Concep ualiza ion, N.M.; me hodology, N.M.; supe ision, N.M.; w i ing— e iew and edi ing, N.M.; w i ing—o iginal d a p epa a ion, A.A.; so wa e, A.A.; da a cu a ion, A.A. All au ho s ha e ead and ag eed o he published e sion o he manusc ip . Funding: This wo k was suppo ed by na ional unds om FCT-Founda ion o Science and Tech- nology (RESEARCH 4 COVID-19): P ojec COMPRIME (Ge o Know Mo e o In e en ion)-ID: 596685735 and P ojec COMPRI_MO (Ge o Know Mo e o In e en ion in he con ex o mobili y)- ID: 613765655. Da a A ailabili y S a emen : The o iginal da a used in he dashboa d s udy is a ailable in he ollowing URL: h ps://co id19.min-saude.p / ela o io-de-si uacao/. The p ocessed da a used in he dashboa d is a ailable in he ollowing URL: h ps://www.comp ime-comp i-mo .com. Con lic s o In e es : The au ho s decla e no con lic o in e es . Re e ences 1. WHO—Wo ld Heal h O ganiza ion. Ten Th ea s o Global Heal h in 2019. 2019. A ailable online: h ps://www.who.in /news- oom/ ea u e-s o ies/ en- h ea s- o-global-heal h-in-2019 (accessed on 19 Sep embe 2020). 2. WHO—Wo ld Heal h O ganiza ion. WHO Di ec o -Gene al’s Opening Rema ks a he Media B ie ing on COVID-19–11 Ma ch 2020. 2020. 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