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Estimating community prevalence of ocular Chlamydia trachomatis infection using pooled polymerase chain reaction testing.

Abstract

Community infection prevalence was estimated using maximum likelihood estimation with data collected from a previously described study. Simulations for communities were performed to determine the accuracy of prevalence estimation using pooled results. The root mean squared error was then used to determine an acceptable inaccuracy in estimates allowing for a pooling strategy to be formed.

Trachoma is the leading cause of blindness from infection worldwide. Treatment programs require accurate Chlamydia trachomatis infection prevalence rates to guide decision making. The use of clinical examination is by far the most common way to monitor activity, but may yield overestimates of infection prevalence. Laboratory testing on individual specimens such as polymerase chain reaction (PCR) is highly sensitive and specific, but prohibitively expensive. Here we demonstrate simulations of pooled PCR results may estimate infection prevalence of an entire community yielding substantial cost savings if pool size is chosen correctly.

Pooling specimens for PCR testing often provides enough data to accurately estimate infection prevalence at the community level.

Results from simulations and empirical data suggest optimum pooling strategies to estimate community infection prevalence while keeping the root mean squared error of the estimate below 2%. Reduction of PCR testing which permits cost savings is shown to be between 5 and 80% given a community infection prevalence below 60%.

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