Adaptive Group Testing Models for Infection Detection of COVID-19

Abstract

Two adaptive group testing models are studied based on zero-error criterion in this paper. Firstly, for the single-stage group testing model, the analytical expression of optimal number of grouping members without integer constraints is given. Secondly, the optimal number of grouping members with integer constraints are given by numerical calculation. Finally, a grouping coefficient-based multistage model and the principles for selecting optimal grouping coefficient are proposed. The results of this paper can help medical institutions to improve group testing efficiency of infection detection of COVID-19.