On an optimal testing strategy for workplace settings operating during the COVID-19 pandemic

Abstract

High quality daily testing for the presence of the SARS-CoV-2 in workplace settings has become part of the standard and mandatory protection measures implemented widely in response to the current pandemic. Such tests are often limited to a small fraction of the attending personnel due to cost considerations, limited availability and processing capabilities and the often cumbersome requirements of the test itself. A maximally efficient use of such an important and frequently scarce resource is clearly required. We here present an optimal testing strategy which minimises the presence of pre-symptomatic and asymptomatic infected members of the population in a workplace setting, derived under a series of simplifying statistical assumptions. These assumptions however, retain many of the generalities of the problem and yield robust results, as verified through a number of numerical simulations. We show that reduction in overall infected-person-days, IPD, by significant percentages can be achieved, for fixed numbers of tests per day of 5% and 10% of the population, of 30% and 50% in the IPD numbers, respectively.