Characterizing the Dynamic of COVID-19 with a New Epidemic Model: Susceptible-Exposed-Symptomatic-Asymptomatic-Active-Removed

Abstract

AbstractThe coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread stealthily and presented a tremendous threat to the public. It is important to investigate the transmission dynamic of COVID-19 to help understand the impact of the disease on public health and economy. While a number of epidemic models have been available to study infectious diseases, they are in-adequate to describe the dynamic of COVID-19. In this paper, we develop a new epidemic model which utilizes a set of ordinary differential equations with unknown parameters to delineate the transmission process of COVID-19. Different from the traditional epidemic models, this model accounts for asymptomatic infections as well the lag between symptoms onset and the confirmation date of infection. We describe an estimation procedure for the unknown parameters in the proposed model by adapting the iterated filter-ensemble adjustment Kalman filter (IF-EAKF) algorithm to the reported number of confirmed cases. To assess the performance of our proposed model, we examine COVID-19 data in Quebec for the period of April 2, 2020 to May 10, 2020 and carry out sensitivity studies under a variety of assumptions. To reflect the transmission potential of an infected case, we derive the basic reproduction number from the proposed model. The estimated basic reproduction number suggests that the pandemic situation in Quebec for the period of April 2, 2020 to May 10, 2020 is not under control.