five

Lake Victoria region block sub-county level risk data

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NIAID Data Ecosystem2026-05-10 收录
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http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.crjdfn3dj
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The health risks of climate change need to be identified to inform the prioritization of adaptation efforts. This is particularly true within low- and middle-income countries (LMICs) with limited resources, heterogenous climates, and varying degrees of social vulnerability. In Kenya, diarrheal disease is one of the leading causes of death and identifying risk factors of diarrheal disease is critical. This research aims to characterize factors associated with a high risk of diarrheal disease in western Kenya by developing a risk index based on the Intergovernmental Panel on Climate Change (IPCC) risk framework.  We developed a conceptual model of risk factors based on prior research with risk factors grouped into the four components of the IPCC risk framework: hazard, exposure, and vulnerability (which is comprised of sensitivity and adaptive capacity). We obtained 30 data elements corresponding to the four components for 99 sub-counties in 14 western Kenya counties. We conducted principal component analysis (PCA) to develop a risk index for diarrheal disease. Our risk index aligns with epidemiological literature, including precipitation, temperature, water sanitation and hygiene (WASH), sensitive populations, education, poverty, and health facilities. Within counties, we found that the risk varied substantially, and a geographic cluster of high-risk sub-counties was identified. Our findings should be useful for policymakers and health officials in Kenya to prioritize efforts to prepare communities for health impacts of climate change. The process may be useful for standardizing approaches to assessing the risk of climate-sensitive health outcomes.
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2025-09-10
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