A dynamic model of COVID-19: contagion and implications of isolation enforcement

Abstract

We present a dynamic model that produces day-to-day changes in key variables due to the COVID-19 contagion: the number of ever infected people, currently infected, deaths, healed, and infected people who require hospitalization. The model is carefully calibrated to Spanish data and we conduct simulation exercises to study the role of isolation measures to contain the virus spread. We find that virus containment from isolation exhibits increasing returns. Our model simulations show that the State of Alarm intervention of the Spanish government on March 14th, 2020 reduces deaths by almost 85%, and lowers the maximum number of infected people who need daily hospitalization by a factor of 1/12. The simulations also indicate that both the timing and the intensity of the isolation enforcement are key for the evolution of the virus spread and the smoothing of the hospitalization needs.