Skip to content
DraconiticResearch
Search Sources API
201,683 studies31 sourcesUpdated 51 min ago
Peer-reviewedCC BY 4.0PLOS Water

Impact of weather and season on stored water contamination and infant diarrhea in climate-vulnerable, urban Mozambique

  • Rebecca S. Kann1
  • Sydney Hubbard2
  • Jedidiah Snyder3
  • Sandy McGunegill4
  • Bacelar Muneme5
  • João Luis Manuel6
  • Lance A. Waller
  • Rassul Nalá
  • Karen Levy
  • Matthew C. Freeman
  • the PAASIM Study Authorship Consortium
6 affiliations
  1. 1Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, United States of America
  2. 2Rollins School of Public Health, Gangarosa Department of Environmental Health, Emory University, Atlanta, Georgia, United States of America
  3. 3WE Consult, Maputo, Mozambique
  4. 4Beira Operations Research Center, Beira, Mozambique
  5. 5Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GeorgiaUnited States of America
  6. 6Instituto Nacional de Saúde (INS), Ministério de Saúde, Maputo, República de Moçambique
Read full textPDFDOICite

Abstract

Diarrhea remains a leading cause of morbidity and mortality for children under five, despite reductions in its global burden in recent decades. However, climate change, and its associated meteorological conditions - heavy rainfall, temperature, flooding - has the potential to impede or reverse progress, particularly in low-income, climate-vulnerable communities. Better characterization of the impact of weather and season on drinking water quality and child health will allow us to capture the anticipated health burden associated with climate change. We characterized the associations of weather and season on infant diarrhea and household stored water quality in Beira, Mozambique. We collected data from mother-child dyads in the third trimester of pregnancy and when the infant was 3-, 6-, 9-, and 12-months old. Using modified Poisson regression mixed effects models, we evaluated associations between weather (i.e., season, heavy rainfall events, ambient temperature, and flooding) and (1) household stored water quality and (2) infant diarrhea. Rainy season (aPR: 1.49; 95% CI: [1.34, 1.67]) was associated with a higher prevalence of stored water contamination, and higher temperatures were associated with a higher prevalence of stored water contamination during the dry season only (aPR: 1.14; 95% CI: [1.03, 1.27]). Source water contamination was associated with a higher prevalence of stored water contamination during both rainy (aPR: 1.32; 95% CI: [1.11, 1.56]) and dry seasons (aPR: 1.56; 95% CI: [1.22, 2.00]). Rainy season (aPR: 1.18; 95% CI: [1.01, 1.38]) was associated with a higher prevalence of infant diarrhea, as was higher temperatures, though only during the dry season (aPR: 1.19; 95% CI: [1.05, 1.35]). This study highlights the importance of addressing household water contamination for reducing the burden of diarrheal disease as well as the importance of understanding the seasonal and weather-dependent variation in both water contamination and infant diarrhea.

Related

  1. Skillful Seasonal Tropical Cyclone Prediction with AI Weather--Climate Models Forced by Dynamically Predicted SSTs
    Hiroyuki Murakami, Baoqiang Xiang
    EarthArXivPreprintPublisher termsFull textAtmospheric science & meteorologyEarthArXiv
  2. Asymmetric response of vegetation NPP to extreme climate over a vulnerable karst Region in Southwest China
    Zhiyuan Yang, Jingjie Geng, Kang Xu +2
    PLOS OnePeer-reviewedCC BY 4.0Full textEcologyGeneral chemistryPLOSPMC
  3. Station-specific thunderstorm forecasting using climate predictors with seasonal decomposition analysis in Bangladesh’s most vulnerable regions
    Mohammad Mahboob Hussain Khan, Amrin Binte Ahmed, Adisha Dulmini +6
    PLOS OnePeer-reviewedCC BY 4.0Full textAtmospheric science & meteorologyGeophysics & seismologyPLOS
  4. Weather forecasting in a changing climate: the rise of AI and Machine learning?
    Florence Rabier, Andrew Brown, Matthew Chantry +1
    Journal of the European Meteorological Society.Peer-reviewedCC BY7 citedAtmospheric science & meteorologyOpenAlex
  5. A neural network-based Universal Thermal Climate Index for reliable global thermal-stress classification across extreme weather
    Bikem Pastine, Milan Klöwer, Tianning Tang +2
    arXivPreprintCC BY 4.0Full textAtmospheric science & meteorologyarXiv

Cite

BibTeXRIS
BibTeX
@article{kann2026impact,
  title = {{Impact of weather and season on stored water contamination and infant diarrhea in climate-vulnerable, urban Mozambique}},
  author = {Rebecca S. Kann and Sydney Hubbard and Jedidiah Snyder and Sandy McGunegill and Bacelar Muneme and João Luis Manuel and Lance A. Waller and Rassul Nalá and Karen Levy and Matthew C. Freeman and the PAASIM Study Authorship Consortium},
  journal = {PLOS Water},
  year = {2026},
  month = sep,
  doi = {10.1371/journal.pwat.0000599},
  url = {https://journals.plos.org/water/article?id=10.1371/journal.pwat.0000599},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Impact of weather and season on stored water contamination and infant diarrhea in climate-vulnerable, urban Mozambique
AU  - Rebecca S. Kann
AU  - Sydney Hubbard
AU  - Jedidiah Snyder
AU  - Sandy McGunegill
AU  - Bacelar Muneme
AU  - João Luis Manuel
AU  - Lance A. Waller
AU  - Rassul Nalá
AU  - Karen Levy
AU  - Matthew C. Freeman
AU  - the PAASIM Study Authorship Consortium
PY  - 2026
DA  - 2026/09/22
JO  - PLOS Water
DO  - 10.1371/journal.pwat.0000599
UR  - https://journals.plos.org/water/article?id=10.1371/journal.pwat.0000599
AB  - Diarrhea remains a leading cause of morbidity and mortality for children under five, despite reductions in its global burden in recent decades. However, climate change, and its associated meteorological conditions - heavy rainfall, temperature, flooding - has the potential to impede or reverse progress, particularly in low-income, climate-vulnerable communities. Better characterization of the impact of weather and season on drinking water quality and child health will allow us to capture the anticipated health burden associated with climate change. We characterized the associations of weather and season on infant diarrhea and household stored water quality in Beira, Mozambique. We collected data from mother-child dyads in the third trimester of pregnancy and when the infant was 3-, 6-, 9-, and 12-months old. Using modified Poisson regression mixed effects models, we evaluated associations between weather (i.e., season, heavy rainfall events, ambient temperature, and flooding) and (1) household stored water quality and (2) infant diarrhea. Rainy season (aPR: 1.49; 95% CI: [1.34, 1.67]) was associated with a higher prevalence of stored water contamination, and higher temperatures were associated with a higher prevalence of stored water contamination during the dry season only (aPR: 1.14; 95% CI: [1.03, 1.27]). Source water contamination was associated with a higher prevalence of stored water contamination during both rainy (aPR: 1.32; 95% CI: [1.11, 1.56]) and dry seasons (aPR: 1.56; 95% CI: [1.22, 2.00]). Rainy season (aPR: 1.18; 95% CI: [1.01, 1.38]) was associated with a higher prevalence of infant diarrhea, as was higher temperatures, though only during the dry season (aPR: 1.19; 95% CI: [1.05, 1.35]). This study highlights the importance of addressing household water contamination for reducing the burden of diarrheal disease as well as the importance of understanding the seasonal and weather-dependent variation in both water contamination and infant diarrhea.
SN  - 2767-3219
ER  -