Modelling COVID-19 Transmission in the United States through Interstate and Foreign Travels and Evaluating Impact of Governmental Public Health Interventions

Abstract

Background: The first case of COVID-19 was reported in Wuhan, China in December 2019. The disease has spread to 210 countries and has been labeled as a pandemic by WHO. Modelling, evaluating, and predicting the rate of disease transmission is crucial for epidemic prevention and control. Our aim is to assess the impact of interstate and foreign travel and public health interventions implemented by the United States government in response to the Covid-19 pandemic. Methods: A disjoint mutually exclusive compartmental model is developed to study the transmission dynamics of the novel coronavirus. A system of non-linear differential equations was formulated and the basic reproduction number R0 was computed. The stability of the model was evaluated at the equilibrium points. Optimal controls were applied in the form of travel restrictions and quarantine. Numerical simulations were conducted. Results: Analysis shows that the model is locally asymptomatically stable, at endemic and foreigners free equilibrium points. Without any mitigation measures, infectivity and subsequent hospitalization of the population increase while placing interstates individuals and foreigners under quarantine, decreases the chances of exposure and subsequent infection, leading to an increase in the recovery rate. Conclusion: Interstate and foreign travel restrictions, in addition to quarantine, help in effectively controlling the epidemic.

Interstates of Infection: Preliminary Investigations of Human Mobility Patterns in the COVID‐19 Pandemic

“…It appears that the degrees of social connection and mobility are the key factors for interstate spread. Our results are also supported by the findings of Shah and associates, demonstrating the crucial role of road travel restrictions in reducing COVID‐19 transmission 30 . Clearly, our results and extant research drive us to inquire about more intricate patterns of human interaction and transmission and explanatory measures beyond population density.…”

“…In the future, it will be conducive to adapt the methodology of Fang and associates and conduct proportional hazards survival analyses for the effects of interstate intersection, RUCC, and other human mobility measures on COVID‐19 arrival events 13 . Research in this area may support stronger travel restrictions and social distancing directives in the future 30 . Together, these analyses can be used to develop a more robust understanding of the spatiotemporal patterns of COVID‐19.…”