Effects of Interregional Travels and Vaccination in Infection Spreads Simulated by Lattice of SEIRS Circuits
Yukio Ohsawa, Teruaki Hayashi, Sae Kondo

TL;DR
This study extends the SEIRS model to include interregional travel and vaccination strategies, revealing that optimizing vaccine distribution based on conditional entropy can more effectively control infection spread, even with high travel activity.
Contribution
The paper introduces a novel SEIRS-based simulation incorporating interregional movement and vaccination prioritization, highlighting the effectiveness of entropy-based vaccine allocation strategies.
Findings
Maximizing conditional entropy Hc improves vaccine efficiency.
Travel across regions can suppress infection spread with high vaccination pace.
Entropy-based vaccination outperforms effective reproduction number-based strategies.
Abstract
The SEIRS model, an extension of the SEIR model for analyzing and predicting the spread of virus infection, was further extended to consider the movement of people across regions. In contrast to previous models that con-sider the risk of travelers from/to other regions, we consider two factors. First, we consider the movements of susceptible (S), exposed (E), and recovered (R) individuals who may get infected and infect others in the destination region, as well as infected (I) individuals. Second, people living in a region and moving from other regions are dealt as separate but interacting groups with respect to their states, S, E, R, or I. This enables us to consider the potential influence of movements before individuals become infected, difficult to detect by testing at the time of immigration, on the spread of infection. In this paper, we show the results of the simulation where…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Mathematical and Theoretical Epidemiology and Ecology Models · Evolution and Genetic Dynamics
