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• W2058611910 abstract "Much of our knowledge of the epidemiology and demography of HIV epidemics in Africa is derived from models fit to sparse, non-representative data. These often average over age and other important dimensions, rarely quantify uncertainty, and typically do" @default.
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• W2058611910 date "2012-12-12" @default.
• W2058611910 modified "2023-10-16" @default.
• W2058611910 title "Estimates of Age-Specific Reductions in HIV Prevalence in Uganda: Bayesian Melding Estimation and Probabilistic Population Forecast with an HIV-enabled Cohort Component Projection Model" @default.
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• W2058611910 doi "https://doi.org/10.4054/demres.2012.27.26" @default.
• W2058611910 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3819033" @default.
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