Modeling and computation of multistep batch testing for infectious diseases.

ABSTRACT: We propose a mathematical model based on probability theory to optimize COVID-19 testing by a multistep batch testing approach with variable batch sizes. This model and simulation tool dramatically increase the efficiency and efficacy of the tests in a large population at a low cost, particularly when the infection rate is low. The proposed method combines statistical modeling with numerical methods to solve nonlinear equations and obtain optimal batch sizes at each step of tests, with the flexibility to incorporate geographic and demographic information. In theory, this method substantially improves the false positive rate and positive predictive value as well. We also conducted a Monte Carlo simulation to verify this theory. Our simulation results show that our method significantly reduc

SUBMITTER: Ahn H 

PROVIDER: S-EPMC8251120 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature