Data from: Do the health benefits of boiling drinking water outweigh the negative impacts of increased indoor air pollution exposure?
Data files
Mar 25, 2024 version files 5 MB
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Air_WASH_Data_Output.zip
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README.md
Abstract
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 indoor air pollution (IAP) 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 1110 DALYs and 368 DALYs per 10,000 people for adults and children <5 years 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, apart from fewer avoided DALYs in children due to different demographics. In both countries, for households with high baseline IAP from existing solid fuel use, adding water boiling to cooking on a given stove was associated with a limited increase in IAP DALYs due to the log-linear dose-response curves. Boiling, even at low effectiveness, was associated with net DALY reductions for medium- and high-risk water, even if using unclean stoves/fuels. Replacing traditional stoves with improved stoves coupled with effective boiling practices significantly reduced total DALYs.
Discussion: Boiling water generally resulted in a net decrease in DALYs. Future efforts should empirically measure health outcomes from IAP vs. diarrhea associated with boiling drinking water using field studies with different boiling methods and stove types.
README: 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
Author and contact details withheld until after publication
Data Generation
Data was generated from June 2020 to March 2024 using R. The code will be made available after publication.
Funding Source
This work was supported by the National Science Foundation (award #1743741)
Sharing/Access Information:
We palce no restrictions on the use this data, however, please cite this repository, and the preprint/paper once published.
Links to publications that cite or use the data:
Will add preprint link and publication link here once they are published.
Description of the data and file structure
This dataset includes the csv output files and a link to the github with R code.
Description of CSV Files
The output files are in the folder Air_WASH_Data_Output. This includes a folder for each country: Uganda and Vietnam
For each country, the following folders are provided:
Averages
Averages includes:
- DALYs: The folder called DALYs includes average values and standard deviation for adults and children, and also differences from the baseline. PM contains files with the average 24 hour PM2.5 concentrations.
- Stove Number: Average number of stoves needed to produce the energy needed daily
- Water: Average and standard deviation of drinking water DALYs for different boiling scenarios
MC_Output
This folder contains the output from the Monte Carlo iterations
The folder includes folders for the fuels used:
- Charcoal
- Clean
- Gasifier
- Improved
- LPG
Within each folder for each fuel there are the following folders:
- Cooking
- Water Heating
- Water Heating Cooking
This includes the Monte Carlo outputs for each energy use scenario for children and adults.
The drinking water folder contains monte carlo for each of the boiling scenarios:
- Good
- Ineffective
- Lab
- Loweffective
- Moderate
- Negative
- NoBoiling
- Verygood
This includes the Monte Carlo outputs for children and adults for safe, low, medium, and high levels of E. coli contaminated water.
Sharing/Access information
Links to other publicly accessible locations of the data:
The R code is available on a public github page, which also includes a readme. This will be made available after publication.
Sources of Input Data
Input data was from the literature, and details are provided in our paper preprint and in the Github.
Code/Software
The csv files can be open in excel.
The code was writen in R
R version 4.3.1 (2023-06-16 ucrt) -- "Beagle Scouts"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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.
Usage 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.