Nedelman J
Department of Mathematical Sciences, Clemson University, South Carolina 29634-1907.
Biometrics. 1988 Sep;44(3):635-55.
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.
对加基项目的数据进行分析,以评估误诊如何影响恶性疟原虫估计流行率。推导并应用了三种考虑专家易犯错性的双重抽样模型。这些模型不同程度地纳入了有关血液中寄生虫密度的信息。对流行率估计中的误差进行了量化,并研究了其对日历时间、年龄、流行率和密度的依赖性。发现流行率和平均密度是误差的良好预测指标,后者更佳。研究了双重抽样模型对设计类似于加基项目的流行病学调查的意义。