Calculating the prevalence of soil-transmitted helminth infection through pooling of stool samples: Choosing and optimizing the pooling strategy

Prevalence is a common epidemiological measure for assessing soil-transmitted helminth burden and forms the basis for much public-health decision-making. Standard diagnostic techniques are based on egg detection in stool samples through microscopy and these techniques are known to have poor sensitivity for individuals with low infection intensity, leading to poor sensitivity in low prevalence populations. PCR diagnostic techniques offer very high sensitivities even at low prevalence, but at a greater cost for each diagnostic test in terms of equipment needed and technician time and training. Pooling of samples can allow prevalence to be estimated while minimizing the number of tests performed. We develop a model of the relative cost of pooling to estimate prevalence, compared to the direct approach of testing all samples individually. Analysis shows how expected relative cost depends on both the underlying prevalence in the population and the size of the pools constructed. A critical prevalence level (approx. 31%) above which pooling is never cost effective, independent of pool size. When no prevalence information is available, there is no basis on which to choose between pooling and testing all samples individually. We recast our model of relative cost in a Bayesian framework in order to investigate how prior information about prevalence in a given population can be used to inform the decision to choose either pooling or full testing. Results suggest that if prevalence is below 10%, a relatively small exploratory prevalence survey (10–15 samples) can be sufficient to give a high degree of certainty that pooling may be relatively cost effective.Author summary: Current diagnostic methods for assessing prevalence of soil-transmitted helminths (STHs) largely rely on microscopic visualization of helminth eggs, an inexpensive but insensitive method of detection. However, growing interest in going beyond control to break transmission of STH through mass drug administration will require highly sensitive assays to detect the low intensity infections that occur when prevalence is low within a population. Molecular tools, such as real-time PCR, offer the required sensitivity, but depend on well-equipped laboratories and adequately trained technicians. In addition, current assays are relatively expensive to perform at the scale required for surveys. Sample pooling is a technique that can be used to estimate prevalence from a set of samples, while potentially employing fewer tests for a given sample size, reducing cost. The decision in favour of or against pooling will determine how samples are collected, properly stored and analysed, and that needs to be established early in the study or program design process. Our work identifies the key determinants on which this decision should be made, what information is needed to make the choice and how the decision can be made.