Febrile Disease Epidemiology and Geospatial Modeling in Southern Sri Lanka
As a subproject under the collaboration between Ruhuna University in Sri Lanka and Duke University, this study focused on the identification of socioeconomic and ecological determinants of febrile illness in Galle district. We integrated socioeconomic data from local government, ecological data from national geographic information system (GIS) database, and febrile patients' epidemiologic data from clinical investigation. The integrated database was prepared using GIS techniques and validated via field visits. Missing population data were simulated through Bayesian imputation. While the febrile disease risk is not measurable in the current study, social and ecological predictors of disease distribution (proportion of specific disease in all cases) were identified for the enrolled Teaching Hospital Karapitiya (THK) patients. These predictors are potentially the determinants of febrile disease in Galle. Due to the limitation of single-center clinical sampling, patient travel distance was highly associated with patient visits, thus, it became a strong confounder in analyses. After adjusted for the confounders, a set of patients' social/ecological exposures were found to be associated with dengue, leptospirosis, URTI, LRTI, gastroenteric infection, and/or undifferentiated febrile illness.
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