SEIR-FMi: A coronavirus disease epidemiological model based on intra-city movement, inter-city movement and medical resource investment

Abstract

In this paper, we propose a coronavirus disease (COVID-19) epidemiological model called SEIR-FMi (Susceptible-Exposed-Infectious-Recovery with Flow and Medical investments) to study the effects of intra-city population movement, inter-city population movement, and medical resource investment on the spread of the COVID-19 epidemic. We theoretically derived the reproduction number of the SEIR-FMi model by using the next-generation matrix method and empirically simulate the individual impacts of population movement and medical resource investment on epidemic control. We found that intra- and inter-city population movements will increase the risk of epidemic spread, and the effect of inter-city population movement on low-risk areas is higher than that on high-risk areas. Increasing medical resource investment can not only speed up the recover rate of patients but also reduce the growth rate of infected cases and shorten the spread duration of the epidemic. We collected data on intra-city population movement, inter-city population movement, medical resource investment, and confirmed cases in the cities of Wuhan, Jingzhou, and Xiangyang, Hubei Province, China, from January 15 to March 15, 2020. Using the collected data, we validated that the proposed SEIR-FMi model performs well in simulating the spread of COVID-19 in the three cities. Meanwhile, this study confirms that three non-pharmaceutical interventions, namely community isolation, population mobility control, and medical resource aid, applied during the epidemic period are indispensable in controlling the spread of COVID-19 in the three cities.