Antonella Basso, Rachel Gaither and Hannah Thomas
Abstract
Pooled testing strategies for infectious diseases like COVID-19 are important in the context of diagnostic test shortages, where it may be more efficient to use pooled samples from multiple patients instead of individual tests for each patient. However, the optimal number of patients per pool is not immediately obvious and may change depending on disease prevalence and test characteristics like sensitivity. For this reason, we develop an interactive application with R that allows users to find the optimal number of patients per pool given various patient, disease and test parameters. The simulation used to build our Shiny App is based on Simulation of Pool Testing to Identify Patients with Coronavirus Disease 2019 Under Conditions of Limited Test Availability (Cherif et al. 2020). Additionally, we ensure to construct the app such that users may input parameters of interest; visualize test efficiency, cost savings, and probability as well as estimated number of false negative results; and download the resulting data for their own use.
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