Let the “A” in WASH Stand for Air: Integrating Research and Interventions to Improve Household Air Pollution (HAP) and Water, Sanitation and Hygiene (WaSH) in Low-Income Settings.
Summary
We argue that bringing these two areas together would improve the effectiveness and efficiency of interventions to reduce the massive disease burden associated with HAP and poor WaSH, including pneumonia and diarrhea, the leading killers of young children in low-income countries. Research can advance greater coordination of these areas by demonstrating their interactions and wider impacts on well-being as well as the potential for programmatic synergies. Integrated solutions to clean households and communities can benefit from the contribution in multiple disciplines, including economics and policy analysis; business and finance; engineering and technology; lab sciences, environmental health, and biomedical sciences; and behavioral and implementation sciences.
Effectiveness of a rural sanitation programme on diarrhoea, soil-transmitted helminth infection, and child malnutrition in Odisha, India: a cluster-randomised trial
Objective
Methods
Burden Of Disease From Inadequate Water, Sanitation And Hygiene In Low‐And Middle‐Income Settings: A Retrospective Analysis Of Data From 145 Countries
Objective
To estimate the burden of diarrhoeal diseases from exposure to inadequate water, sanitation and hand hygiene in low‐ and middle‐income settings and provide an overview of the impact on other diseases.
Methods
For estimating the impact of water, sanitation and hygiene on diarrhoea, we selected exposure levels with both sufficient global exposure data and a matching exposure‐risk relationship. Global exposure data were estimated for the year 2012, and risk estimates were taken from the most recent systematic analyses. We estimated attributable deaths and disability‐adjusted life years (DALYs) by country, age and sex for inadequate water, sanitation and hand hygiene separately, and as a cluster of risk factors. Uncertainty estimates were computed on the basis of uncertainty surrounding exposure estimates and relative risks.