Optimal group testing strategy for the mass screening of SARS-CoV-2

Fengfeng Huang, Pengfei Guo, Yulan Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

We analyze the group testing strategy that maximizes the efficiency of the SARS-CoV-2 screening test while ensuring its effectiveness, where the effectiveness of group testing guarantees that negative results from pooled samples can be considered presumptive negative. Two aspects of test efficiency are considered, one concerning the maximization of the welfare throughput and the other concerning the maximization of the identification rate (namely, identifying as many infected individuals as possible). We show that compared with individual testing, group testing leads to a higher probability of false negative results but a lower probability of false positive results. To ensure the test effectiveness, both the group size and the prevalence of SARS-CoV-2 must be below certain respective thresholds. To achieve test efficiency that concerns either the welfare throughput maximization or the identification rate maximization, the optimal group size is jointly determined by the test accuracy parameters, the infection prevalence rate, and the relative importance of identifying infected subjects. We also show that the optimal group size that maximizes the welfare throughput is weakly smaller than the one that maximizes the identification rate.

Original languageEnglish
Article number102689
JournalOmega (United Kingdom)
Volume112
DOIs
Publication statusPublished - Oct 2022

Keywords

  • Group testing
  • Mass screening
  • Test sensitivity
  • Test specificity

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

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