A Metapopulation Seir Model with Asymptomatic Individuals Based On Human Mobility Patterns

In the post-pandemic era, new variants of COVID-19 continue to emerge and spread within communities across various regions, underscoring the importance of epidemic control and prevention. However, previous research has largely overlooked migration behaviors and individual awareness. In this paper, we propose a Susceptible-Exposed-Asymptomatic-Symptomatic-Recovered (SEI<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sup>I<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sup>R) model with a self-protection mechanism that simulates the impact of awareness in the metapopulation network. The proposed model incorporates analytical expressions for each state, derived from human mobility patterns using the microscopic Markov chain approach (MMCA). Simulation results highlight the significant influence of initial mobility rates and population size on disease transmission. We present an example of a real transportation network for metapopulations to illustrate its effectiveness in depicting epidemic dynamics.