Weather extremes and diarrheal disease: findings from a multi-city study in the Asia Pacific Region
Abstract
Background: Changes in weather patterns including increasing extreme weather events tied to ongoing climate change is impacting burden of diarrheal disease, yet there is a paucity of data regarding how this risk varies across large urban areas within the high-risk Asia Pacific Region (APR). We investigated the association between weather extremes (temperature, precipitation) and risk of diarrheal disease burden in large metropolitan areas of APR.
Method: We obtained diarrheal disease records from 17 cities located across the APR, including cities in Nepal, Taiwan, Vietnam, India, Singapore, and Indonesia. We used a distributed lag non-linear model to investigate the association between exposure to weather extremes (high: 95th percentile and low: 5th percentile of temperature and precipitation) and diarrheal disease burden. City-specific risk estimates were subsequently pooled using multivariate random-effects meta-analysis.
Results: A total of 10,358,987 diarrheal disease cases were included. Considerable heterogeneity was observed in temperature- and precipitation-related associations across cities. At the pooled level, neither extreme low nor extreme high temperature was significantly associated with diarrheal disease, with RRs of 1.02 (95% CI: 0.88–1.19) and 1.09 (95% CI: 0.96–1.24), respectively; pooled associations with extreme precipitation were also not statistically significant. However, extreme high temperature was associated with increased risk in Ahmedabad (RR: 2.32; 95% CI: 1.43–3.74), while extreme low temperature was associated with increased risk in Kaohsiung (RR: 1.83; 95% CI: 1.39–2.41). Latitude-specific analyses suggested stronger associations with extreme low temperature at higher latitudes and somewhat stronger associations with extreme high temperature at lower latitudes.
Conclusion: Our data point to significant spatial heterogeneity in diarrheal disease burden associated with exposure to extreme temperatures and precipitation. Public health adaptation strategies designed to help communities adapt to health threats of climate change need to account for such heterogeneity.
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BibTeX
@article{andhikaputra2026weather,
title = {{Weather extremes and diarrheal disease: findings from a multi-city study in the Asia Pacific Region}},
author = {Gerry Andhikaputra and Ayushi Sharma and Hao He and Chuansi Gao and Raul Cruz-Cano and Veena Iyer and Meghnath Dhimal and Dang Thi Anh Thu and Antony Azarsyah and Bhavin Solanki and Amir Sapkota and Yu-Chun Wang},
journal = {BMC Public Health},
year = {2026},
month = oct,
doi = {10.1186/s12889-026-30120-6},
url = {https://link.springer.com/article/10.1186/s12889-026-30120-6},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Weather extremes and diarrheal disease: findings from a multi-city study in the Asia Pacific Region
AU - Gerry Andhikaputra
AU - Ayushi Sharma
AU - Hao He
AU - Chuansi Gao
AU - Raul Cruz-Cano
AU - Veena Iyer
AU - Meghnath Dhimal
AU - Dang Thi Anh Thu
AU - Antony Azarsyah
AU - Bhavin Solanki
AU - Amir Sapkota
AU - Yu-Chun Wang
PY - 2026
DA - 2026/10/28
JO - BMC Public Health
DO - 10.1186/s12889-026-30120-6
UR - https://link.springer.com/article/10.1186/s12889-026-30120-6
AB - Background: Changes in weather patterns including increasing extreme weather events tied to ongoing climate change is impacting burden of diarrheal disease, yet there is a paucity of data regarding how this risk varies across large urban areas within the high-risk Asia Pacific Region (APR). We investigated the association between weather extremes (temperature, precipitation) and risk of diarrheal disease burden in large metropolitan areas of APR. Method: We obtained diarrheal disease records from 17 cities located across the APR, including cities in Nepal, Taiwan, Vietnam, India, Singapore, and Indonesia. We used a distributed lag non-linear model to investigate the association between exposure to weather extremes (high: 95th percentile and low: 5th percentile of temperature and precipitation) and diarrheal disease burden. City-specific risk estimates were subsequently pooled using multivariate random-effects meta-analysis. Results: A total of 10,358,987 diarrheal disease cases were included. Considerable heterogeneity was observed in temperature- and precipitation-related associations across cities. At the pooled level, neither extreme low nor extreme high temperature was significantly associated with diarrheal disease, with RRs of 1.02 (95% CI: 0.88–1.19) and 1.09 (95% CI: 0.96–1.24), respectively; pooled associations with extreme precipitation were also not statistically significant. However, extreme high temperature was associated with increased risk in Ahmedabad (RR: 2.32; 95% CI: 1.43–3.74), while extreme low temperature was associated with increased risk in Kaohsiung (RR: 1.83; 95% CI: 1.39–2.41). Latitude-specific analyses suggested stronger associations with extreme low temperature at higher latitudes and somewhat stronger associations with extreme high temperature at lower latitudes. Conclusion: Our data point to significant spatial heterogeneity in diarrheal disease burden associated with exposure to extreme temperatures and precipitation. Public health adaptation strategies designed to help communities adapt to health threats of climate change need to account for such heterogeneity.
SN - 1471-2458
ER -