COVID-19 and other viruses: Holding back its spreading by massive testing

The experience of Singapore and South Korea makes it clear that under certain circumstances massive testing is an effective way for containing the advance of the COVID-19. In this paper, we propose a modified SEIR model which takes into account tracing and massive testing, proving theoretically that more tracing and testing implies a reduction of the total number of infected people in the long run. We apply this model to the spreading of the first wave of the disease in Spain, obtaining numerical results. After that, we introduce a heuristic approach in order to minimize the COVID-19 spreading by planning effective test distributions among the populations of a region over a period of time. As an application, the impact of distributing tests among the counties of New York according to this method is computed in terms of the number of saved infected individuals.

Automated summary

The experiences of Singapore and South Korea suggest that massive testing is effective in containing the spread of COVID-19. A modified SEIR model, along with a heuristic approach, can theoretically reduce the number of infected individuals and guide efficient testing distribution strategies.