Abstract
The rapid spread of COVID-19 throughout the world, has led most of the affected countries to close their borders and implement some form of lockdown. Six months after the pandemic started, many countries made decisions tending to relax the lockdown, although without a vaccine or treatment capable of confronting SARS-CoV-2 infection, the situation could be reversed at any time. In this context, the aim of this work was to propose a decision algorithm that will allow to optimize asymptomatic case detections and strategically manage quarantine to prevent the spread of the virus and drive the transition to a managed new normal. This tentative proposal was developed for optimizing and ordering the number of tests for the detection of SARS-CoV-2, analyzing composite samples (group analysis) combining with those samples individually taken from asymptomatic members of cohorts of interest. Cohorts were defined according to their critical role in society and/or their vulnerability. The algorithm includes variables such as cohort priority, number of cohort members in the analysis groups, intra-and intergroup contact, vulnerability to contagion due to the activity performed, and time elapsed since last testing. The proposed tool was illustrated with defined hypothetical cohorts, in which, for the sake of simplification, only one analysis group was considered. The application of this tool allowed to establish in a rational way a priority order to test critical groups in society. Furthermore, this tool would help to optimize resources, reducing the impact on a region's health, society, and economy.