Evidence map›Paper›PMID 41575992›Full record

ArticlePloS one2026

Water treatment and E. coli in drinking water: Household responses to (invisible) water quality risks.

Akito Kamei, Bhowmik Sujey Soori

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Akito KameiSchool of Government and Economics, Universidad Panamericana, Ciudad de México, México.ORCID https://orcid.org/0000-0003-3327-9231
Bhowmik Sujey SooriEconomics Department, University of Arizona, Tucson, Arizona, United States of America.ORCID https://orcid.org/0009-0006-5518-8487

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn 2024, an estimated 4 billion people lacked access to safely managed drinking water, with the greatest risks for vulnerable groups such as young children. The objective of this paper is to 1) document the share of households exposed to E. coli contamination at the water source, 2) examine whether households are more likely to treat their water when the source is E. coli contaminated, and 3) assess how household water treatment relates to E. coli levels in stored drinking water.

methodsThis paper analyzes nationally representative Multiple Indicator Cluster Surveys (MICS) data from 59,633 households in low- and middle-income countries across 25 countries in Sub-Saharan Africa, Latin America, and Asia, all of which conducted standardized water-quality tests both at the source and in stored household drinking water. The main analysis documents how household water-treatment behavior differs by the level of E. coli contamination in their water source using regression methods by controlling for the country-specific fixed effects and household characteristics.

resultsThe study reveals that 78% of households do not treat their water, While 20% relying on sources with high E. coli contamination levels (>100 MPN/100 ml). Despite this risk, the presence of E. coli is positively associated with a higher likelihood of treating water by just 3 to 5 percentage points, depending on contamination levels, from an average baseline of 21%. The association is stronger in Latin America and weaker in Africa. Moreover, analysis of stored household drinking water reveals that a substantial share of households that report treating their water still exhibit moderate to high E. coli contamination in stored samples.

conclusionHouseholds' water-treatment behavior shows only a modest association with the invisible risk of contamination, and many households still have E. coli contaminated drinking water even after treating it. These results highlight the need for WASH strategies that go beyond promoting access to treatment-specifically, strategies that inform households about contamination risks and emphasize correct and consistent application to ensure safe drinking water.

Indexed as

Drinking WaterEscherichia coliWater MicrobiologyWater PurificationWater QualityFamily CharacteristicsHumansWater SupplyDrinking Water

Identifiers

PMID41575992
PMCPMC12829840

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.