Modelling the Health and Economic Impact of Scaling Up Diabetes Screening Strategies to Achieve the WHO Global Diabetes Compact Target for Diagnosis in Kenya:The Kenya Kisukari Model.
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AI plain-English summaryIn Kenya, roughly half of all adults with type 2 diabetes do not know they have it, and this PhD project will build a computer model to determine which screening strategies could change that. This matters because undiagnosed diabetes leads to severe complications—kidney failure, blindness, amputations—that hit patients and Kenya’s overstretched health system hard. The World Health Organization has set a target for timely diagnosis, but no one has yet modelled which screening approach would be most cost-effective and feasible for Kenya’s specific context. The researcher will first review diabetes screening programmes across Africa, then interview Kenyan policymakers and clinicians about what works on the ground. Using that data, they will build a mathematical and economic model that compares different screening strategies—for example, targeting high-risk groups versus population-wide testing—and estimates their impact on early diagnosis, health outcomes, and costs. If successful, the model will give Kenya’s Ministry of Health a practical, evidence-based tool to prioritise screening investments. The immediate impact is on policy, not patients’ daily lives, but better policy should mean fewer people discover their diabetes only after a crisis.
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