This document summarizes trends in water, sanitation, and hygiene (WASH)-related mortality in sub-Saharan Africa from 1950 to 2050. It finds that childhood mortality rates have declined across many world regions, including in sub-Saharan Africa. However, WASH-related mortality rates and deaths still remain high in many sub-Saharan African countries and are projected to decline only moderately by 2050 without accelerated interventions and policy changes to improve access to water and sanitation. The document models and compares projections of WASH-related mortality rates and deaths across country groupings in sub-Saharan Africa.

1. WASH-related
Mortality Trends in
Sub-Saharan Africa
August 28, 2014

2. 2
Contextual Factors
& Initial Conditions
{IWRM}
Policy (mix)
Institutions
Water Law
Organizations
Process
Integration/Coordination
Decentralization
Participation
WRM
IWRM
Water resources
endowment/distribution/level
of development
Level of economic
development Nation/RB
Political factors (Democracy
National/local levels,
Decentralization, Governance)
Social/cultural factors (local
experience with self
governance and service
provision)
etc
Mohamed Ait Kadi – Zaragoza 0708

3. Improved Water: Total (Urban Rural)
UNICEF and WHO. 2012. Progress on drinking water and sanitation: 2012 update.
Available at: http://www.wssinfo.org/fileadmin/user_upload/resources/JMP-report-2012-en.pdf Accessed on 28 Jan 2013.

4. Some Good News!
Childhood mortality rates are declining the
rate of decline is accelerating.
Across 21 regions of the world, rates of
neonatal, post-neonatal, and childhood
mortality are declining, and there is evidence
of accelerating declines from 2000 to 2010
compared with 1990 to 2000 (including Sub-
Saharan Africa).
Rajaratnam et al. (2010). “Neonatal, post-neonatal, childhood, and under-5 mortality
for 187 countries, 1970–2010: a systematic analysis of progress towards
Millennium Development Goal 4.” The Lancet. May 24.

5. Water sanitation-related mortality
1950-2050, by world region

6. WASH-related Mortality– China, India, Brazil,
Nigeria (1950-2050)
0.25
0.20
0.15
0.10
0.05
0.00
1950
1960
1970
1980
1990
2000
2010
2020
2030
2040
2050
WSH Mortality Rate (%)
Year
China
India
Brazil
Nigeria

7. Emerging Threshold Countries in SSA
Source: Radalet 2010
o 17 emerging countries: dramatic
changes in economic growth,
poverty reduction, and political
accountability since the mid-1990s.
o Avg. annual GDP growth of 3.2%,
between 1996 and 2008 (all 17
emerging countries)
o 6 threshold countries: considerable
but less dramatic change

8. WASH Mortality Categories
Moderate Mortality;
Insufficient Decline
High Mortality
Low Mortality
High Mortality
Stagnant Moderate decline
Moderate Mortality;
Sufficient Decline

9. High Mortality
High Mortality
Stagnant Moderate decline
o Highest WASH mortality rates, both
at baseline and in projections
o Stagnant progress in reducing
WASH mortality in some counties
(mostly fragile and oil states)
o Moderate decline in other
countries (mostly threshold and
emerging economies)

10. Moderate Mortality,
Insufficient Decline (Little Progress)
o Moderate WASH mortality rates,
for the Sub-Saharan Africa region
o Progress is insufficient to achieve
South Asian levels of WASH
mortality by 2050
Moderate Mortality;
Insufficient Decline

11. Moderate Mortality,
Sufficient Decline (Good Progress)
o Moderate WASH mortality rates,
for the Sub-Saharan Africa region
o Progress is sufficient to achieve
South Asian levels of WASH
mortality by 2050.
o Mostly threshold and emerging
economies
Moderate Mortality;
Sufficient Decline

12. Low Mortality
o Historically low WASH mortality
rates, comparable to South Asia
o By 2050, WASH mortality projected
to be near zero
Low Mortality

13. WASH Modeling Framework
Population
Growth
Economic
Growth
WASH
Coverage
WASH-Related
Mortality
Economic
Benefits
-
+
- +
That’s good! That’s good!

14. Baseline assumptions: representative countries
Population

15. Baseline assumptions: representative countries
GDP per Capita

16. Best and Worst Case Assumptions:
Nigeria
Base Best Worst
Avg. Annual GDP Growth 4.1% 4.5% 3.7%
Coverage
Piped Water Coverage GDP Elasticity 9.5 14.5 4.5
Piped Water Coverage % Urban Elasticity 0.35 0.6 0.1
Improved Water Coverage GDP Elasticity 4.5 9 0
Improved Water Coverage % Urban Elasticity 0.3 0.5 0.1
Improved Sanitation Coverage GDP Elasticity 8 14 2
Improved Sanitation Cov. % Urban Elasticity 0.45 0.8 0.1
Mortality
WSH Mortality GDP Elasticity -0.2 -0.3 -0.1
WSH Mortality Piped WatSan Elasticity -0.02 -0.03 -0.01
WSH Mortality Log Piped WatSan Elasticity -0.5 -0.7 -0.3
WSH Mortality Improved Water Elasticity -0.0275 -0.045 -0.01

17. Results …

18. WASH Mortality Categories:
Representative Countries
Moderate Mortality;
Insufficient Decline
High Mortality
Low Mortality
High Mortality
Stagnant
Democratic Rep.
of Congo
Moderate decline
Ethiopia
Moderate Mortality;
Sufficient Decline
Nigeria
Kenya South Africa

19. WASH Mortality Categories
Moderate Mortality;
Insufficient Decline
High Mortality
Low Mortality
High Mortality
Stagnant
Burundi
Central African Rep.
Chad
DRC
Guinea Bissau
Niger
Somalia
Moderate decline
Angola
Burkina Faso
Ethiopia
Liberia
Mali
Sierra Leone
Moderate Mortality;
Sufficient Decline
Benin
Cameroon
Comoros
Congo
Cote d'Ivoire
Ghana
Guinea
Madagascar
Malawi
Mauritania
Mozambique
Nigeria
Rwanda
Sudan
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Botswana
Equatorial
Guinea
Eritrea
Gambia
Kenya
Lesotho
Namibia
Senegal
Swaziland
Cape Verde
Gabon
Mauritius
Seychelles
South Africa

20. WASH Mortality Rate by Country Grouping

21. WASH Mortality Rate: Projections

22. WASH-related Deaths by country grouping

23. Total WASH-Related Deaths: Projections

24. Population without Improved WS coverage
(Representative Countries)

25. Model Overview
Collect secondary data
Assemble country-level data sets and estimate empirical relationships
using regression analysis
Coverage with water
sanitation services
WASH-related
mortality
Other control
variables
Assess associations with
WASH-related mortality rates
Assess associations with piped
and improved water and
sanitation coverage
Adjust coverage estimates for
piped water + sewer
Simulate outcomes (1990-2050)
WASH-related
mortality rates
Piped service + improved
water coverage
Calculate WASH-related
deaths (1990-2050)
Calculate WTP to avoid
mortality (1990-2050)
Sensitivity analyses
on model
parameters

26. Baseline assumptions: representative countries
Improved Water Coverage

27. Economic Population Projections
Drivers of coverage and WASH-related
mortality

28. Population by country grouping

29. GDP by country grouping

30. GDP per Capita, by country grouping

31. Projections: Wash-mortality Rates,
Wash-related Death

32. Projections by Country Groupings

33. WASH Mortality Rate, by category

34. Best/Worst Cases

35. Best/Worst Cases

36. Oil and Mineral Exporters

37. WASH Mortality Rate, 2008
Oil and Mineral Exporters

38. WASH Mortality Rate, 2008
Oil and Mineral Exporters

39. WASH Deaths, 2008
Oil and Mineral Exporters