Abstract
Widescale testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is recognized as a key element of surveillance and outbreak control in the coronavirus disease 2019 (COVID-19) pandemic. The practical challenges, however, have often led to testing only symptomatic individuals and their close contacts. As many countries plan for a cautious relaxation of social restrictions, more effective approaches for widescale testing are increasingly important. Early in the COVID-19 pandemic, laboratories in several countries demonstrated the feasibility of detecting SARS-CoV-2 infection by pooled testing, which combines the specimens from several individuals. Since no further testing is needed for individuals in a negative pool, there is potential for greater efficiency of testing. Despite validations of the accuracy of the results and the efficiency in testing specific groups, the benefits of pooling are less acknowledged as a population surveillance strategy that can detect new disease outbreaks without posing restrictions on entire societies. Pooling specimens from natural clusters, such as school classes, sports teams, workplace colleagues and other social networks, would enable timely and cost-effective widescale testing for SARS-CoV-2. The initial result would be readily translatable into action in terms of quarantine and isolation policies. Clusters of uninfected individuals would be quickly identified and immediate local lockdown of positive clusters would be the appropriate and sufficient action while retesting those individuals. By adapting to the social networks of a population, pooled testing offers a cost-efficient surveillance system that is synchronized with quarantine policies that are rational, risk-based and equitable.