Data from: Health trade-offs of boiling drinking water with solid fuels: A modeling study
- 1. North Carolina State University
Description
Background: Billions of the world's poorest households are faced with the lack of access to both safe drinking water and clean cooking. One solution to microbiologically contaminated water is boiling, often promoted without acknowledging the additional risks incurred from indoor air degradation from using solid fuels.
Objectives: This modeling study explores the tradeoff of increased air pollution from boiling drinking water under multiple contamination and fuel use scenarios typical of low-income settings.
Methods: We calculated the total change in disability-adjusted life years (DALYs) from household air pollution (HAP) and diarrhea from fecal contamination of drinking water for scenarios of different source water quality, boiling effectiveness, and stove type. We used Uganda and Vietnam, two countries with a high prevalence of water boiling and solid fuel use, as case studies.
Results: Boiling drinking water reduced the diarrhea disease burden by a mean of 1100 DALYs and 367 DALYs per 10,000 people for those under and over 5 years of age in Uganda, respectively, for high-risk water quality and the most efficient (lab-level) boiling scenario, with smaller reductions for less contaminated water and ineffective boiling. Similar results were found in Vietnam, though with fewer avoided DALYs in children under 5 due to different demographics. In both countries, for households with high baseline HAP from existing solid fuel use, adding water boiling to cooking on a given stove was associated with a limited increase in HAP DALYs due to the log-linear exposure-response curves. Boiling, even at low effectiveness, was associated with net DALY reductions for medium- and high-risk water, even with unclean stoves/fuels. Use of clean stoves coupled with effective boiling significantly reduced total DALYs.
Discussion: Boiling water generally resulted in net decreases in DALYs. Future efforts should empirically measure health outcomes from HAP vs. diarrhea associated with boiling drinking water using field studies with different boiling methods and stove types.
Notes
The code is written in R (R Core Team (2021). R: A language and environment for statistcial computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.The data files can be opened in excel.
Funding provided by: National Science Foundation
ROR ID: https://ror.org/021nxhr62
Award Number: 1743741
Methods
The goal of this study was to develop a framework to compare health risks. We focus on two countries, Uganda and Vietnam to show how the framework is used. We synthesized established modeling tools to build an analytical framework to compare health impacts from IAP and fecally-contaminated drinking water at the household level, using DALYs as the primary metric to compare multiple risks. Input variables were selected from the best available data in the literature. We used DALYs to quantify health burdens because they account for morbidity with differential disease severity and mortality. Quantitative Microbial Risk Assessment (QMRA) models are commonly used to determine the risk associated with consuming water from a particular water source (Havelaar & Melse, 2003). For IAP, the population attributable fraction based on a dose-response curve for individual diseases is used to calculate the burden of disease (Asikainen et al., 2016; Pillarisetti et al., 2016).
The first module is called the water risk module, which uses a QMRA to calculate the DALYs from drinking water contaminated by fecal matter before and after treatment by boiling. The second module is the air risk module. This uses an indoor box model to quantify the PM2.5 concentrations for different stoves and uses combined with the Household Air Pollution Intervention Tool (HAPIT) to quantity the DALYs associated with IAP under various scenarios. We designed the model to be used for any country. However, we selected Uganda and Vietnam as case study countries as they are in distinct regions, have different population demographics, and high prevalences of boiling among household water treatment users.
The R code was designed to run a Monte Carlo simulation for different scenarios and produce outputs of indoor air pollution concentrations, and drinking water and air pollution DALYs in csv files.
Files
Air-WASH.zip
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Additional details
Related works
- Is cited by
- 10.1101/2024.03.22.24304348 (DOI)
- Is source of
- 10.5061/dryad.9zw3r22jz (DOI)