Optimal and worst examination strategies for COVID-19

Abstract

AbstractCoronavirus disease 2019 (COVID-19) is an emerging threat to the whole world, and every government is seeking an optimal solution. However, none of them have succeeded, and they have only provided series of natural experiments. Although simulation studies seem to be helpful, there is no model that addresses the how much testing to be conducted to minimise the emerging infectious disease outbreaks. In this study, we develop a testing susceptible, infectious, exposed, recovered, and dead (testing-SEIRD) model using two discrete populations inside and outside hospitals. The populations that tested positive were isolated. Through the simulations, we examined the infectious spread represented by the number of cumulative deaths, hospitalisations, and positive tests, depending on examination strategies, testing characteristics, and hospitalisation capacity. We found all-or-none responses of either expansion or extinction of the infectious spreads, depending on the rates of follow-up and mass testing, which represent testing the people identified as close contacts with infected patients using follow-up surveys and people with symptoms, respectively. We also demonstrated that there were optimal and worst examination strategies, which were determined by the total resources and testing costs. The testing-SEIRD model is useful in making decisions on examination strategies for the emerging infectious disease outbreaks.