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Saving a Life-Year and Reaching MDG 4 with Investments in Water and Sanitation: A Cost-Effective Policy?

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Abstract

Using household survey data from 40 developing countries, we estimate the mortality impact of improved water and sanitation access. We find that the average mortality reduction achievable by investment in water and sanitation infrastructure is 8 and 22 deaths per 1000 children born for basic and advanced technologies, respectively. These reductions account for 11 per cent (basic technologies) to 32 per cent (advanced technologies) of the gap between current child mortality rates and the 2015 target set in the Millennium Development Goal 4. Our estimates suggest that full household coverage with water and sanitation infrastructure could lead to a reduction of 0.6 to 1.7 million child deaths per year in the developing world. The average cost per life-year saved is about 30 per cent of developing countries’ annual GDPs per capita for high-end technologies and about 80 per cent of annual per capita GDP for basic water and sanitation infrastructure.

A partir d’une base de données recueillies dans 40 pays en développement, nous estimons l’impact, sur la mortalité, d’une amélioration de l’accès à l’eau et de la qualité de celle ci. Nous constatons que la réduction moyenne de la mortalité atteignable grâce aux investissements dans des infrastructures d’accès à l’eau et d’assainissement est comprise entre 8 (technologies de base) et 22 décès (technologies avancées) pour 1000 enfants nés. Ces taux de réduction représentent entre 11 per cent (technologies de base) et 32 per cent (technologies avancées) de l’écart entre le taux de mortalité infantile actuel et celui fixé pour 2015 dans l’Objectif 4 du Millénaire pour le Développement. Selon nos estimations, assurer l’accès de tous les ménages aux infrastructures d’eau et d’assainissement permettrait d’éviter entre 0.6 et 1.7 million de décès infantiles par an dans le monde en développement. Le coût moyen par année de vie sauvée est d’environ 30 per cent du PNB annuel par habitant des pays en développement, si des technologies haut de gamme sont adoptées, et d’environ 80 per cent du PNB annuel par habitant si des infrastructures de base sont installées.

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Notes

  1. Unfortunately, we are not able to analyse the effect of water treatment or hygiene promotion interventions in this study. The data at hand (DHS surveys) do not provide consistent information across countries on households’ hygiene behaviour or application of water treatment technologies.

  2. A similar methodology is applied in Günther and Fink (2011) and Fink et al (2011).

  3. See Table 2 for a detailed definition of improved water and sanitation technology.

  4. A STATA do file with the applied coding is available from the authors on request.

  5. http://www.wssinfo.org/definitions/ladders.html.

  6. Several DHS do not distinguish between protected and unprotected wells and springs. Whenever it was not clear from the data whether a spring or well was improved, we made the assumption that it was unimproved. We therefore might have slightly underestimated access to improved water technologies.

  7. We do not include an interaction term of water and sanitation technologies in our final specification because this term was found to be insignificant in various empirical estimations: this result is in line with recent literature on water, sanitation and diarrhoea (Fewtrell et al, 2005; Fewtrell et al, 2007; Waddington and Snilstveit, 2009).

  8. Child mortality reflects the likelihood of a child born in period t dying in the period t to t+5. Under the simplifying assumption that the previous cohorts are of approximately the same size as the one in a given year, it is easy to see that deaths prevented in a given year can be expressed as in equation (4).

  9. For reasons of simplicity, we assume that all children do not die before the age of 5. As mortality in this age range is generally clustered around the earlier ages, this is clearly a conservative assumption.

  10. Even though only 75 per cent of the households in our sample currently include women in their childbearing years, unpredictable changes in household composition over time led us to include all households without infrastructure.

  11. We could not find more recent cross-regional data on water and sanitation infrastructure costs.

  12. A sensitivity check, using lower bound investment costs and upper bound durability estimates, can be obtained from the authors on request.

  13. We do not include operation and maintenance costs to treat households that already have access to improved water and sanitation infrastructure and households that do not have access yet equally. A sensitivity check, including operation and maintenance costs, is available from the authors on request.

  14. The odds ratio of 0.932 corresponds to the odds of dying below the age of 5 in any given year with improved sanitation divided by the odds of dying without improved sanitation. Improved sanitation thereby decreases the odds of dying by 6.8 per cent: (1–0.932) × 100.

  15. The under-5 mortality estimates reported by the WHO in 2005 are 262 for Niger and 235 for Liberia. But these estimates seem to be based on earlier survey data. For details, see http://www.who.int/healthinfo/statistics/mortchildmortality/en/index.html.

  16. A sensitivity check to Table 5 – taking the upper and lower bound of the 95 per cent confidence interval of the point estimates in Table 4 – are available from the authors on request. Taking the upper bound of the 95 per cent confidence interval, the impact of improved water and sanitation doubles (in comparison to Table 5). Taking the lower bound of the 95 per cent confidence interval, simple water and sanitation technologies do not have any effect on child mortality, whereas private water and sanitation connections still significantly reduce child mortality rates (even if the impact is only a third of the figures presented in Table 5).

  17. The mean under-5 child mortality rate in our sample is 94 (per 1000), compared with 90 in the developing world (World Population Prospects: http://esa.un.org/wpp/unpp/panel_indicators.htm). Access to improved water and sanitation is 76 and 33 per cent in our sample, compared with 75 and 40 per cent in the developing world (JMP: http://www.wssinfo.org/data_esimates/table/). Estimates are population weighted.

  18. Including all countries of Africa, Latin America (Caribbean) and Asia. Excluding China and the Middle East.

  19. This result also indicates smaller effects of water and sanitation programmes over time. See Fink et al (2011) for a discussion.

  20. http://www.who.int/choice/costs/CER_thresholds/en/index.html.

  21. A sensitivity analysis to explore the impact of cost and durability assumptions on cost-effectiveness can be obtained from the authors on request.

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Acknowledgements

The authors thank the World Bank's Knowledge for Change Program for funding this research. The views and findings in this article are those of the authors and not necessarily those of the World Bank.

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Authors and Affiliations

  1. ETH Zürich, Zürich, Switzerland

    Isabel Günther

  2. Harvard School of Public Health, Boston, MA.

    Günther Fink

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  1. Isabel Günther
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  2. Günther Fink
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Appendix

Appendix

Table A1

Table A1 Water and sanitation coverage
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Table A2

Table A2 Logistic regression: Diarrhoea within the last 2 weeks
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Günther, I., Fink, G. Saving a Life-Year and Reaching MDG 4 with Investments in Water and Sanitation: A Cost-Effective Policy?. Eur J Dev Res 25, 129–153 (2013). https://doi.org/10.1057/ejdr.2012.24

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