Health trade-offs of boiling drinking water with solid fuels: A modeling study

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 b...,
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., ..., 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., # Data from: Health trade-offs of boiling drinking water with solid fuels: A modeling study 

Air and WASH health risk comparison code and output files
Access this dataset on Dryad (DOI: 10.5061/dryad.9zw3r22jz)

## Introduction

We developed a code to calculate the health impacts of boiling drinking water with solid fuels This code in R is written to compare the health risks from drinking water and indoor air pollution when boiling drinking water with various types of fuels. It can be run for various countries. Right now, data to run for two focus countries, Uganda and Vietnam, is provided. Data for additional countries can be added.

## Authors

Emily Floess, Ayse Ercumen, Angela Harris, Andy Grieshop, NC State University

## Data Generation

Data was generated from June 2020 to October 2024 using R.

## Description of the data and file structure

This dataset includes the csv output files and a folder with the R code.

### Description of Output CSV Files: Air\_WASH\_Data\_Output...,