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Diarrhea Patterns and Climate: A Spatiotemporal Bayesian Hierarchical Analysis of Diarrheal Disease in Afghanistan

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  • 1 Department of Epidemiology, University of Louisville School of Public Health and Information Sciences, Louisville, Kentucky;
  • | 2 Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut;
  • | 3 Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut
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Subject to a high burden of diarrheal diseases, Afghanistan is also susceptible to climate change. This study investigated the spatiotemporal distribution of diarrheal disease in the country and how associated it is with climate variables. Using monthly aggregated new cases of acute diarrhea reported between 2010 and 2016 and monthly averaged climate data at the district level, we fitted a hierarchical Bayesian spatiotemporal statistical model. We found aridity and mean daily temperature were positively associated with diarrhea incidence; every 1°C increase in mean daily temperature and 0.01-unit change in the aridity index were associated with a 0.70% (CI: 0.67%, 0.73%) increase and a 4.79% (CI: 4.30%, 5.26%) increase in the risk of diarrhea, respectively. Average annual temperature, on the other hand, was negatively associated, with a 3.7% (CI: 3.74%, 3.68) decrease in risk for every degree Celsius increase in annual average temperature. Temporally, most districts exhibited similar seasonal trends, with incidence peaking in summer, except for the eastern region where differences in climate patterns and population density may be associated with high rates of diarrhea throughout the year. The results from this study highlight the significant role of climate in shaping diarrheal patterns in Afghanistan, allowing policymakers to account for potential impacts of climate change in their public health assessments.

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Author Notes

Address correspondence to Mohammad Y. Anwar, Department of Epidemiology, University of Louisville School of Public Health and Information Sciences, 485 E. Gray St., Louisville, KY 40202. E-mail: m0anwa02@louisville.edu

Financial support: J. L. W. was supported by CTSA grant numbers UL1 TR001863 and KL2 TR001862 from the National Center for Advancing Translational Science (NCATS), components of the National Institutes of Health (NIH), and NIH roadmap for Medical Research. V. E. P. was supported by the National Institutes of Health/National Institute of Allergy and Infectious Diseases (NIH/NIAID) grant R01AI112970. The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the official view of NIH.

Disclosure: This study used aggregate de-identified data and was therefore exempt from ethics committee review.

Authors’ addresses: Mohammad Y. Anwar, Department of Epidemiology, University of Louisville School of Public Health and Information Sciences, Louisville, KA, E-mail: m0anwa02@louisville.edu. Joshua L. Warren, Department of Biostatistics, Yale School of Public Health, New Haven, CT, E-mail: joshua.warren@yale.edu. Virginia E. Pitzer, Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, E-mail: virginia.pitzer@yale.edu.

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