The Prevalence of Malaria in Garki, Nigeria: Double Sampling with a Fallible Expert

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Abstract
Data from the Garki Project are analyzed to assess how misdiagnosis affects the estimated prevalence of Plasmodium falciparum. Three double-sampling models that account for the fallibility of the expert are derived and applied. The models incorporate information about the density of parasites in the blood to varying degrees. The error in the estimation of prevalence is quantified; and its dependence on calendar time, age, prevalence, and density is investigated. Prevalence and average density are discovered to be good predictors of the error, with the latter being better. Implications of the double-sampling models for the design of epidemiological surveys similar to the one in Garki are investigated.