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首页|Socio-demographic, not environmental, risk factors explain fine-scale spatial patterns of diarrheal disease in Ifanadiana, rural Madagascar

Socio-demographic, not environmental, risk factors explain fine-scale spatial patterns of diarrheal disease in Ifanadiana, rural Madagascar

Socio-demographic, not environmental, risk factors explain fine-scale spatial patterns of diarrheal disease in Ifanadiana, rural Madagascar

来源:medRxiv_logomedRxiv
英文摘要

Abstract Diarrheal disease (DD) is responsible for over 700,000 child deaths annually, the majority in the tropics. Due to its strong environmental signature, DD is amenable to precision health mapping, a technique that leverages spatial relationships between socio-ecological variables and disease to predict hotspots of disease risk. However, precision health mapping tends to rely heavily on data collected at coarse spatial scales over large spatial extents. There is little evidence that such methods produce operationally-relevant predictions at sufficiently fine enough spatio-temporal scales (e.g. village level) to improve local health outcomes. Here, we use two fine-scale health datasets (<5 km) collected from a health system strengthening initiative in Ifanadiana, Madagascar and identify socio-ecological covariates associated with childhood DD. We constructed generalized linear mixed models including socio-demographic, climatic, and landcover variables and estimated variable importance via multi-model inference. We find that socio-demographic variables, and not environmental variables, are strong predictors of the spatial distribution of disease risk at both an individual and commune-level spatial scale. Specifically, a child’s age, sex, and household wealth were the primary determinants of disease. Climatic variables predicted strong seasonality in DD, with the highest incidence in the colder, drier months of the austral winter, but did not predict spatial patterns in disease. Importantly, our models account for less than half of the total variation in disease incidence, suggesting that the socio-ecological covariates identified as important via global precision health mapping efforts have reduced explanatory power at the local scale. More research is needed to better define the set of conditions under which the application of precision health mapping can be operationally useful to local public health professionals.

Cordier Laura F、Haruna Justin、Randriamanambtsoa Marius、Raza-Fanomezanjanahary Estelle M、Razafinjato B¨|n¨|dicte R.、Evans Michelle V、Garchitorena Andres、Ihantamalala Felana、Drake John M、Miller Ann C、Bonds Matthew H、Murdock Courtney C

PIVOT, RanomafanaPIVOT, RanomafanaNational Institute of StatisticsMinistry of Health, MadagascarPIVOT, RanomafanaOdum School of Ecology, University of Georgia||Center for Ecology of Infectious Diseases, University of GeorgiaPIVOT, Ranomafana||MIVEGEC, Univ. Montpellier, CNRS, IRDDepartment of Global Health and Social Medicine, Harvard Medical School||PIVOT, RanomafanaOdum School of Ecology, University of Georgia||Center for Ecology of Infectious Diseases, University of GeorgiaDepartment of Global Health and Social Medicine, Harvard Medical SchoolDepartment of Global Health and Social Medicine, Harvard Medical School||PIVOT, RanomafanaOdum School of Ecology, University of Georgia||Center for Ecology of Infectious Diseases, University of Georgia||Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia

10.1101/2020.04.02.20051151

医药卫生理论预防医学社会与环境

diarrheal diseaseprecision health mapping

Cordier Laura F,Haruna Justin,Randriamanambtsoa Marius,Raza-Fanomezanjanahary Estelle M,Razafinjato B¨|n¨|dicte R.,Evans Michelle V,Garchitorena Andres,Ihantamalala Felana,Drake John M,Miller Ann C,Bonds Matthew H,Murdock Courtney C.Socio-demographic, not environmental, risk factors explain fine-scale spatial patterns of diarrheal disease in Ifanadiana, rural Madagascar[EB/OL].(2025-03-28)[2025-08-02].https://www.medrxiv.org/content/10.1101/2020.04.02.20051151.点此复制

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