Abstract
Short-term human movements play a major part in the transmission and control of COVID-19, within and between countries. Such movements are necessary to be included in mathematical models that aim to assist in understanding the transmission dynamics of COVID-19. A two-patch basic mathematical model for COVID-19 was developed and analyzed, incorporating short-term human mobility. Here, we modeled the human mobility that depended on its epidemiological status, by the Lagrangian approach. A sharp threshold for disease dynamics known as the reproduction number was computed. Particularly, we portrayed that when the disease threshold is less than unity, the disease dies out and the disease persists when the reproduction number is greater than unity. Optimal control theory was also applied to the proposed model, with the aim of investigating the cost-effectiveness strategy. The findings were further investigated through the usage of the results from the cost objective functional, the average cost-effectiveness ratio (ACER), and then the infection averted ratio (IAR).