RESUMO
The inclusion of the human mobility aspect is essential for understanding the behavior of COVID-19 spread, especially when millions of people travel across borders near Eid Al-Fitr. This study aims at grasping the effect of mass exodus among regions on the active cases of COVID-19 in a mathematical perspective. We construct a multi-region SIQRD (Susceptible-Infected-Quarantined-Recovered-Death) model that accommodates the direct transfer of people from one region to others. The mobility rate is estimated using the proposed Dawson-like function, which requires the Origin-Destination Matrix data. Assuming only susceptible, unapparent infected, and recovered individuals travel near Eid Al-Fitr, the rendered model is well-depicting the actual data at that time, giving either a significant spike or decline in the number of active cases due to the mass exodus. Most agglomerated regions like Jakarta and Depok City experienced the fall of active cases number, both in actual data and the simulated model. However, most rural areas experienced the opposite, like Bandung District and Cimahi City. This study should confirm that most travelers originated from big cities to the rural regions and scientifically justifies that massive mobility affects the COVID-19 transmission among areas.
