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Impact of water, sanitation, and hygiene indicators on enteric viral pathogens among under-5 children in low resource settings

2025· article· en· W4406159671 on OpenAlexfundno aff
Rina Das, Nasif Hossain, Myron M. Levine, Karen L. Kotloff, Dilruba Nasrin, M. Jahangir Hossain, Richard Omore, Dipika Sur, Tahmeed Ahmed, Robert F. Breiman, Shah M. Faruque, Matthew C. Freeman

Bibliographic record

VenueThe Science of The Total Environment · 2025
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersMedical Research CouncilInternational Centre for Diarrhoeal Disease Research, BangladeshForeign, Commonwealth and Development OfficeUK Research and InnovationGlobal Affairs CanadaBill and Melinda Gates Foundation
KeywordsSanitationHygieneEnteric virusEnvironmental healthEnteric bacteriaMedicineVirologyMicrobiologyBiologyEscherichia coli

Abstract

fetched live from OpenAlex

Poor water, sanitation, and hygiene (WASH) are the primary risks of exposure to enteric viral infection. Our study aimed to describe the role of WASH conditions and practices as risk factors for enteric viral infections in children under 5. Literature on the risk factors associated with all-cause diarrhea masks the taxa-specific drivers of diarrhea from specific pathogens, limiting the application of relevant control strategies. We analyzed data from children enrolled in the Global Enteric Multicenter Study (GEMS) across seven study sites between December 2007 and March 2011 as cases (moderate-to-severe diarrhea: MSD) and asymptomatic controls. MSD was defined as new and acute diarrhea, with at least one of the following criteria for MSD: dehydration based on the study clinician's assessment, dysentery, or hospitalization with diarrhea or dysentery. Multiple logistic regression was used to examine the role of water quality, sanitation access, and hygiene facilities on the enteric viral pathogens adjusted for potential covariates. Among MSD symptomatic children (cases), longer water retrieval time (≥15 vs <15 min) was associated with increased Norovirus (aOR 1.33, 95 % CI 1.08-1.64) and Astrovirus (aOR 1.43, 95 % CI 1.01-2.02); scooping as drinking water retrieval method was associated with lower Rotavirus (aOR 0.77, 95 % CI 0.62-0.96), but higher Adenovirus (aOR 2.3, 95 % CI 1.32-4.11) infection compared to non-users. Among asymptomatic children (controls), consumption of non-tube well drinking water was associated with higher Norovirus infection (aOR 1.38, 95 % CI 1.01-1.89). Longer drinking water retrieval time (≥15 vs <15 min) increased Norovirus (aOR 1.47, 95 % CI 1.21-1.78) and Rotavirus (aOR 1.51, 95 % CI 1.20-1.89) infections. Pouring (aOR 0.51, 95 % CI 0.32-0.83) or scooping drinking water with a cup (aOR: 0.52; 95 % CI: 0.32, 0.86) lower Astrovirus infection; restricted water access (aOR 1.57, 95 % CI 1.21-2.02) higher Rotavirus infection. Handwashing before cooking was associated with lower Astrovirus (aOR 0.64, 95 % CI 0.47-0.88) infection in asymptomatic children. Our analysis did not find a significant effect of poor sanitation on different enteric viral pathogens examined. Norovirus and Astrovirus were detected more commonly in sub-Saharan Africa while Rotavirus was less prevalent than South Asia. Though we found statistically significant associations, we did not observe any overall pattern between WASH and enteric viral pathogens. Our findings provide insights to guide further research on targeted interventions for enteric viral pathogens, responsible for a major burden of pediatric diarrhea globally.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.222
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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