Malaria remains one of the most formidable infectious diseases worldwide, particularly in sub-Saharan Africa, where it overlaps with the HIV epidemic. For many people in highly endemic areas, malaria parasitemia is asymptomatic, however, parasitemia provides a reservoir of parasites that drives malaria transmission. The epidemiology of parasitemia, particularly in older children, adults, and HIV-infected persons, is poorly understood in highly endemic countries, as is the influence of individual predictors of parasitemia such as CD4 count, and use of HIV-associated medications. Leveraging the power of an ongoing study in Nankoma, Uganda, an area with high malaria transmission, we will perform a cross-sectional analysis of community residents (n=10,000) to describe population level parasite prevalence. To measure parasite prevalence, we will collect dried blood spots on each resident, and use loop mediated isothermal amplification (LAMP) on a stratified random sample (n=4,000). We will investigate the influence of HIV status, CD4 count, and use of antiretroviral medications on parasite prevalence, and describe areas of geographic clustering within the community. Subject enrollment and determination of parasite prevalence will take place over 6 months and the analysis will occur over 4 months. The results of this research will provide preliminary data for an NIH mentored K23 award to further describe the epidemiology of malaria-HIV co-infection, and identify targeted interventions to reduce the malaria parasite reservoir in East Africa.