Benchma king WASH T ajec o ies in A ica: A Compa a i e Assessmen o Six Coun y
A che ypes (2000–2022)
h ps://doi.o g/10.5281/zenodo.17676132
Zo Ri omanana Rasoanai o, Uni e si y o An anana i o, ORCID: 0009-0003-0725-3764
Abs ac
Access o sa e d inking wa e and sani a ion emains one o he mos une en de elopmen
ajec o ies ac oss A ica. While policy deba es equen ly highligh in es men gaps o
ins i u ional agmen a ion, ew s udies p o ide a c oss-coun y compa a i e analysis g ounded
in long- e m empi ical ends. This pape benchma ks six A ican coun ies—Senegal,
Mozambique, Ghana, Rwanda, Cô e d’I oi e and Madagasca — ep esen ing dis inc s uc u al
and ins i u ional a che ypes, and examines hei wa e , sani a ion and hygiene (WASH)
ajec o ies om 2000 o 2022. Using ha monised WHO/UNICEF Join Moni o ing P og amme
(JMP) da ase s, he s udy analyses p og ess a es, se ice gaps, u al–u ban dispa i ies, and
he s a is ical ela ionship be ween economic pe o mance and WASH ou comes. The esul s
e eal ou ecu en pa e ns: (i) la ge he e ogenei y in baseline condi ions bu con e ging
policy a ge s; (ii) non-linea p og ess wi h s agna ion in se e al con ex s; (iii) pe sis en u al
de ici s and weak co ela ion be ween GDP pe capi a and WASH pe o mance; and (i )
sani a ion ajec o ies ha gene ally lag behind wa e , al hough some coun ies (no ably
Senegal and Ghana) display as e ela i e gains. A summa y quad an highligh s whe e
his o ical p og ess a es emain insu icien o align wi h SDG6 ajec o ies by 2030. These
indings p o ide an e idence-based compa a i e lens o in o m p io i isa ion, na ional
in es men s a egies and egional moni o ing a chi ec u es, while o e ing a anspa en ,
eplicable amewo k o acking WASH deli e y pe o mance ac oss di e se go e nance
con ex s.
Keywo ds
WASH; SDG6; A ica; d inking wa e ; sani a ion; JMP da a; benchma king; de elopmen
ajec o ies; u al–u ban gap
1. In oduc ion
Access o sa e d inking wa e and sani a ion emains one o he mos pe sis en de elopmen
challenges in A ica. Al hough p og ess has been achie ed since 2000, ajec o ies emain
highly he e ogeneous, shaped by demog aphic p essu es, ins i u ional agmen a ion, iscal
cons ain s and he his o ical con igu a ion o se ice deli e y sys ems (Fos e and B iceño-
Ga mendia, 2010; Meh a, 2014). Exis ing moni o ing amewo ks o en ely on coun y-speci ic
analyses and a ely p o ide s uc u ed c oss-coun y compa isons o long- e m WASH
pe o mance.
This s udy add esses his gap by benchma king six A ican coun ies ep esen ing dis inc
s uc u al a che ypes—Senegal, Mozambique, Ghana, Rwanda, Cô e d’I oi e and
Madagasca . These coun ies span a ange o go e nance models, economic condi ions and
WASH pe o mance p o iles, om ela i ely s ong pe o me s (Rwanda, Senegal, Ghana) o
s uc u ally cons ained sys ems (Mozambique, Cô e d’I oi e, Madagasca ) (Adank e al.,
2014; Wo ld Bank, 2018). Using ha monised JMP da ase s (WHO/UNICEF JMP, 2023), he
analysis examines long- e m ajec o ies in d inking wa e and sani a ion, annual p og ess
a es, s uc u al d i e s o pe o mance and alignmen wi h SDG6 a ge s (Uni ed Na ions,
2015).
The con ibu ion is h ee old. Fi s , i p o ides a ha monised compa a i e da ase o c oss-
coun y benchma king o e mo e han wo decades (Shields e al., 2020). Second, i iden i ies
long- e m pa e ns and quan i ies he SDG6 ajec o y gap using a anspa en , eplicable
me hodology (Hu on and Va ughese, 2016). Thi d, i analyses ins i u ional, demog aphic and
economic d i e s shaping WASH p og ess, d awing on es ablished amewo ks o go e nance
and se ice deli e y (Lockwood and Smi s, 2011; And ews e al., 2017; P i che , 2020; OECD,
2021).
2. Da a and Me hods
2.1. Da a sou ces
The analysis d aws on publicly a ailable da ase s om he WHO/UNICEF Join Moni o ing
P og amme (JMP), using he 2023 ha monised upda es o d inking wa e and sani a ion
indica o s (WHO/UNICEF JMP, 2023). These we e complemen ed by GDP pe capi a
(cons an PPP) om he Wo ld De elopmen Indica o s (Wo ld Bank, 2023), demog aphic and
u al–u ban popula ion dis ibu ions om he UN Depa men o Economic and Social A ai s
(UN DESA, 2022), and selec ed mac o-s uc u al a iables ele an o c oss-coun y
compa ison. The JMP me hodology p o ides globally s anda dised de ini ions and s a is ical
p ocedu es, ensu ing compa abili y ac oss coun ies and o e ime (Bain and o he s, 2014;
WHO/UNICEF JMP, 2023).
2.2. Indica o s
The s udy ocuses on wo co e se ice indica o s de ined by he JMP:
• basic d inking wa e co e age (%),
• basic sani a ion co e age (%),
as pe global moni o ing s anda ds (WHO/UNICEF JMP, 2023). These indica o s p o ide a
consis en and long- e m basis o c oss-coun y benchma king. Annualised p og ess a es
we e compu ed o h ee sub-pe iods—2000–2010, 2010–2015 and 2015–2022— o cap u e
changes in momen um o e ime and iden i y in lec ion poin s ele an o SDG6 alignmen ,
ollowing app oaches used in p e ious longi udinal WASH assessmen s (Smi s and Mo ia y,
2012).
2.3. Ha monisa ion and p ocessing
All JMP se ies we e cleaned, alida ed and ha monised using a ep oducible wo k low aligned
wi h s anda d global moni o ing p o ocols (Shields e al., 2020; WHO/UNICEF JMP, 2023).
Missing obse a ions we e handled h ough in e pola ion ollowing JMP/UN guidelines, wi hou
addi ional model-based adjus men s. GDP and demog aphic se ies we e aligned o ensu e
empo al consis ency and compa abili y ac oss he six coun ies. No coun y-le el e-
es ima ions o pos -hoc co ec ions we e applied. Da a p ocessing was ca ied ou using open-
sou ce s a is ical so wa e, and he ull ep oducibili y package—including sc ip s and
me ada a—is a chi ed in an open-access Zenodo eposi o y.
2.4. Compa a i e me hodology
The compa a i e assessmen ollows a ou -s ep analy ical amewo k:
1. long- e m ajec o ies: e alua ion o 2000–2022 e olu ion in basic d inking wa e and
sani a ion co e age;
2. annualised p og ess pa e ns: compa ison o p og ess a es ac oss h ee sub-pe iods o
de ec accele a ion, s agna ion o e e sals (Smi s and Mo ia y, 2012);
3. SDG6 ajec o y gaps: es ima ion o he di e ence be ween p ojec ed 2030 access le els
(based on his o ical ends) and SDG6 a ge h esholds (Uni ed Na ions, 2015; Hu on and
Va ughese, 2016);
4. s uc u al d i e s: explo a ion o mac o-s uc u al co ela es such as u al sha e, GDP pe
capi a, popula ion densi y and u banisa ion pa e ns, in o med by p e ious egional
diagnos ics (Fos e and B iceño-Ga mendia, 2010; OECD, 2021).
The inal diagnos ic in eg a es hese dimensions in o a p og ess s esidual gap quad an ,
which classi ies coun ies acco ding o he alignmen o hei his o ical ajec o ies wi h SDG6
equi emen s and highligh s whe e accele a ion o sys em e o m is mos needed (Smi s and
Mo ia y, 2012; WHO/UNICEF JMP, 2023).
3. Resul s
3.1. Compa a i e WASH con ex
The coun y compa ison able shows conside able a ia ion in baseline condi ions (Figu e 1).
Ghana and Senegal en e he 2000–2022 pe iod wi h ela i ely high basic d inking wa e
co e age, while Mozambique, Madagasca and Cô e d’I oi e begin wi h much lowe le els.
Rwanda displays in e media e co e age ye s ands ou o i s sani a ion ajec o y. Basic
sani a ion is he mos cons ained dimension ac oss he sample, wi h 2022 alues anging om
14.8% in Madagasca o nea ly 74% in Rwanda. These di e ences help ame he s uc u al
pa hway each coun y ollows o e he pe iod.
3.2. Basic d inking wa e ajec o ies
The d inking wa e ime se ies con i ms s eady p og ess in all six coun ies, bu wi h ma ked
di e ences in pace (Figu e 2):
• Mozambique has he highes long- e m a e age gain (+1.90 pp/yea ).
• Senegal and Ghana p og ess a +1.21 and +1.06 pp/yea , espec i ely.
• Rwanda’s ajec o y emains consis en , hough sligh ly slowe (+0.93 pp/yea ).
• Madagasca ad ances mo e slowly (+0.76 pp/yea ).
• Cô e d’I oi e eco ds he lowes a e (+0.10 pp/yea ), e lec ing ex ended s agna ion.
By 2022, Ghana and Senegal each le els abo e 85%, while Madagasca emains below 55%.
The slopes sugges ha ea ly gains linked o popula ion-dense a eas slow down as mo e
dispe sed u al popula ions become he emaining on ie .
3.3. Basic sani a ion ajec o ies
Sani a ion p og ess emains modes ac oss mos coun ies (Figu e 3):
• Rwanda displays he highes slope (+1.35 pp/yea ).
• Mozambique (+1.25), Senegal (+1.07) and Ghana (+1.04) ollow.
• Cô e d’I oi e (+0.76) and Madagasca (+0.50) ad ance a slowe a es.
Despi e p og ess, la ge sani a ion gaps emain, pa icula ly in u al a eas. Rwanda is he only
case whe e u al sani a ion le els exceed u ban le els in 2022, sugges ing a long- e m
emphasis on communi y-led models. In o he con ex s, sani a ion emains he slowes
dimension, ein o cing i s ole as he key cons ain o SDG6 alignmen .
3.4. Annual p og ess pa e ns
Annual WASH p og ess shows h ee consis en ea u es (Figu e 4):
1. All coun ies ha e imp o ed wa e and sani a ion access since 2000.
2. Wa e ypically p og esses as e han sani a ion, wi h he excep ion o Rwanda whe e
sani a ion su passes wa e .
3. The pace eco ded ac oss he g oup (mos ly be ween 0.7 and 1.3 pp/yea ) emains below
he es ima ed annual gains equi ed o achie e SDG6 by 2030.
This pa e n is isible in Cô e d’I oi e and Madagasca , which combine slow wa e p og ess
and limi ed sani a ion gains.
3.5. SDG6 ajec o y gap
The gap analysis compa es his o ic p og ess wi h he pace equi ed o each uni e sal basic
wa e by 2030 (Figu e 5):
• Madagasca would need o mul iply i s his o ic pace 7.6×.
• Cô e d’I oi e equi es a mul iplica ion ac o o ≥10×.
• Mozambique would need 2.4× i s his o ic pace.
• Rwanda mus each 4.7× i s pas a e.
• Ghana and Sénégal equi e ~1.4×.
The igu es con i m ha business-as-usual ends a e insu icien in mos cases, pa icula ly
whe e u al de ici s domina e.
3.6. Weal h s access
The sca e plo compa ing GDP pe capi a and WASH co e age in 2022 shows a weak linea
associa ion (Figu e 6). Coun ies wi h simila income le els display con as ing access
ou comes— o ins ance:
• Cô e d’I oi e and Ghana ha e compa able GDP le els bu di e ge in co e age.
• Rwanda and Sénégal achie e high access le els despi e mo e modes income.
• Mozambique and Madagasca clus e a low income and low co e age, ye wi h di e en
ajec o ies.
The Pea son co ela ion coe icien is = 0.41, indica ing a weak linea ela ionship (and no
s a is ically meaning ul in such a small sample) be ween GDP pe capi a and a e age basic
WASH co e age ac oss his sample. This con i ms ha income alone does no explain
obse ed pe o mance di e ences.
3.7. S uc u al d i e s
The u al–u ban compa ison shows ha u al de ici s emain a de ining cons ain (Figu e 7):
• la ge wa e gaps in Mozambique, Cô e d’I oi e and Madagasca ;
• la ge sani a ion gaps in all coun ies excep Rwanda;
• Rwanda displays an in e ed pa e n, wi h u al sani a ion su passing u ban le els.
These esul s indica e ha u al se lemen pa e ns, local go e nmen capaci y and supply
chain eliabili y a e key de e minan s o na ional ou comes.
3.8. In es men modelling
Indica i e u al wa e in es men needs in 2022 sugges (Figu e 8):
• Madagasca (~585 M USD) and Mozambique (~522 M USD) equi e he la ges en elopes;
• Cô e d’I oi e (~302 M USD) and Rwanda (~224 M USD) ollow;
• Ghana (~178 M USD) and Senegal (~103 M USD) equi e compa a i ely lowe le els.
Cos ing is based on a simple uni -cos model, p o iding a magni ude es ima e a he han a
ull inancial analysis. I highligh s ha coun ies wi h la ge u al popula ions and low co e age
would need sus ained in es men o accele a e access.
3.9. Summa y quad an
The summa y quad an (Figu e 9: his o ic p og ess s 2030 esidual gap) posi ions:
• Ghana and Senegal in he “highe p og ess, lowe gap” a ea;
• Rwanda in a simila space, wi h a mode a e emaining gap;
• Mozambique shows mode a e p og ess wi h a sizeable gap;
• Madagasca and Cô e d’I oi e in he “low p og ess, high gap” quad an .
This classi ica ion p o ides a s aigh o wa d diagnos ic o iden i y whe e accele a ion is mos
necessa y.
4. Discussion
The analysis sugges s ou s able pa e ns ac oss he six coun ies.
Fi s , d inking wa e ajec o ies show sus ained p og ess bu wi h di e ing slopes.
Mozambique p og esses as es , while Cô e d’I oi e and Madagasca display ex ended
s agna ion pe iods. The shape o he cu es sugges s ha coun ies exhaus “easy gains” ea ly
and encoun e s uc u al cons ain s as he emaining popula ion becomes mo e dispe sed.
Second, sani a ion p og ess emains much slowe han wa e in all con ex s excep Rwanda.
The igu es show ha gains emain inc emen al and ha u al–u ban di ides pe sis . Senegal
and Ghana achie e mo e apid sani a ion inc eases han he es o he g oup, possibly
e lec ing na ional p og ammes and a ge ed policy o ien a ion. Rwanda’s pe o mance in u al
sani a ion is also no ewo hy, wi h u al co e age le els ma ching o exceeding u ban
co e age, which sugges s ha communi y-based app oaches and pe o mance-o ien ed
go e nance can educe disad an ages adi ionally associa ed wi h u al se ings (Rwanda
Minis y o In as uc u e, 2016).
Rwanda’s sani a ion ajec o y appea s o e lec long- e m p og amme con inui y and
s uc u ed communi y-le el engagemen , which dis inguishes i s u al se ice deli e y model
om hose o he o he coun ies in he sample (Rwanda Minis y o In as uc u e, 2016).
Thi d, economic weal h does no p edic WASH ou comes. The GDP–access plo shows
conside able dispe sion. Simila income le els co espond o di e en pe o mance p o iles,
sugges ing ha go e nance a angemen s, u al se lemen pa e ns, and consis ency in
se ice deli e y amewo ks play a cen al ole.
Fou h, u al–u ban gaps a e he dominan s uc u al d i e o unde pe o mance. The ba
cha s con i m ha u al de ici s shape na ional a e ages in all coun ies excep Rwanda. The
magni ude o he equi ed 2030 accele a ion co ela es closely wi h he size o hese u al gaps.
Limi a ions include eliance on JMP se ies in ol ing in e pola ions, absence o subna ional
disagg ega ion, and indica i e in es men modelling ha excludes O&M and clima e- ela ed
cos s. Despi e hese limi a ions, he amewo k emains s able and can be eplica ed ac oss
addi ional coun ies.
5. Conclusion
The upda ed igu es ein o ce ou consis en indings ac oss he six selec ed A ican coun ies.
D inking wa e access has imp o ed o e he las wo decades, bu wi h he e ogeneous
p og ess a es. Coun ies such as Senegal, Ghana and Rwanda show sus ained gains, while
o he s—pa icula ly Madagasca and Cô e d’I oi e— eco d slowe imp o emen s.
Sani a ion emains he mos cons ained dimension, wi h pe sis en u al gaps. Rwanda
p o ides he only example whe e u al sani a ion exceeds u ban le els, highligh ing he
in luence o long- e m communi y-based app oaches.
Economic indica o s do no su icien ly explain pe o mance a ia ion. Coun ies wi h
compa able income le els ollow di e en ajec o ies, poin ing o he ole o ins i u ional
a angemen s, decen alisa ion amewo ks, and se ice deli e y models.
Ru al–u ban dispa i ies de e mine much o he emaining gap. Coun ies wi h la ge dispe sed
u al popula ions equi e subs an ial accele a ion and sus ained inancing o p og ess owa d
SDG6.
The SDG6 gap analysis shows ha his o ical p og ess a es a e insu icien in se e al con ex s,
pa icula ly Madagasca , Cô e d’I oi e and Mozambique. Achie ing uni e sal basic access by
2030 would equi e s uc u al adjus men s and p edic able inancing mechanisms.
This compa a i e e iew p o ides a consis en and eplicable app oach o benchma king
WASH ajec o ies. The me hod can be expanded o o he A ican coun ies and o sa ely
managed se ices, and can inco po a e iscal and clima e dimensions in u u e analyses.
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Figu es and Cap ions
Figu e 1. Compa a i e WASH Analysis: 6 A ican A che ypes (2000–2022)
Compa a i e WASH indica o s o six A ican coun ies in 2022, including a ea, GDP, popula ion, and basic wa e /sani a ion co e age. Coun ies a e o de ed
by sani a ion pe o mance, he main s uc u al cons ain o SDG6 p og ess.
Rwanda and Senegal show s onge ins i u ional ajec o ies, while Madagasca and Cô e d’I oi e ace ch onic s uc u al and u al de ici s. These baseline
con as s ame he in e p e a ion o long- e m WASH ajec o ies.
Figu e 8. Indica i e Ru al Basic Wa e In es men (2022)
Es ima ed u al basic wa e in es men needs (million USD) o close he 2022 co e age gap o uni e sal access.
Madagasca and Mozambique abso b he la ges indica i e en elopes due o la ge u al popula ions and low baseline co e age. These alues ep esen one-
o capi al needs and exclude O&M and clima e- ela ed cos s.
Figu e 9. Summa y Quad an : P og ess s Residual Gap (Basic Wa e )
Diagnos ic quad an compa ing his o ic p og ess a es and p ojec ed 2030 esidual gaps unde a business-as-usual ajec o y.
Madagasca and Cô e d’I oi e combine slow p og ess and la ge esidual gaps, posi ioning hem as highes - isk cases. Ghana, Senegal and Rwanda clus e in
he highe -p og ess, lowe -gap zone.
