Mathematical Modeling of the Transmission Dynamics of COVID-19

• Activity Number: 91 - High Dimensional Data, Causal Inference, Biostats Education, and More
• Type: Contributed
• Date/Time: Monday, August 9, 2021 : 10:00 AM to 11:50 AM
• Sponsor: ENAR
• Author(s): Ruzong Fan*
• Companies: Georgetown University Medical Center (GUMC)
• Keywords: COVID-19; incidence rate; mortality rate; susceptible-infected-recovered models; susceptible-exposed-infected-recovered-deceased models

Abstract

The emergence of COVID-19 demonstrates the importance of understanding the transmission and spread of pandemic. In this project, we consider a susceptible-exposed-infected-recovered-deceased system of differential equations to describe relationship among the number of susceptible individuals, the number of exposed individuals who are transmitted the virus, the number of infected individuals among the exposed people, the number of recovered individuals from the infected, and the number of deaths from the infected in a town or a country. Based on the empirical results of transmission process of COVID-19 in the United States, we consider a few cases of contact rate, incidence rate, recovery rate, and mortality rate to model the transmission and dynamics of the virus. Numerical analysis and analytical method are used to explore the dynamics and prediction of the pandemic.