Detection and isolation of asymptomatic individuals can make the difference in COVID-19 epidemic management

Mayorga, Lía; García Samartino, Clara; Flores, Gabriel; Masuelli, Sofía; Sánchez, María Victoria; Mayorga, Luis S.; Sánchez, Cristián Gabriel

Mathematical modeling of infectious diseases is a powerful tool for the design of management policies and a fundamental part of the arsenal currently deployed to deal with the COVID-19 pandemic. Here we present a compartmental model for the disease that can provide healthcare burden parameters allowing to infer possible containment and suppression strategies, explicitly including asymptomatic individuals. The main conclusion of our work is that efficient and timely detection and isolation of these asymptomatic individuals can have dramatic effects on the effective reproduction number and healthcare burden parameters. This intervention can provide a valuable tool complementary to other non-pharmaceutical interventions to contain the epidemic.