Influence of network structure on infectious disease control

Nariyuki Nakagiri; Hiroki Yokoi; Yukio Sakisaka; Kei-ichi Tainaka; Kazunori Sato; Nariyuki Nakagiri; Hiroki Yokoi; Yukio Sakisaka; Kei-ichi Tainaka; Kazunori Sato

doi:10.3934/mbe.2025034

Mathematical Biosciences and Engineering

2025, Volume 22, Issue 4: 943-961. doi: 10.3934/mbe.2025034

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Influence of network structure on infectious disease control

1.
School of Human Science and Environment, University of Hyogo, Himeji 670-0092, Japan
2.
Fisheries Resources Institutes (FRI), Japan Fisheries Research and Education Agency, 2-14-4 Fukuura, Kanazawa, Yokohama, Kanagawa 236-8648, Japan
3.
Division of Early Childhood Care and Education, Nakamura Gakuen University Junior College, Fukuoka, 814-0198, Japan
4.
Department of Mathematical and Systems Engineering, Shizuoka University, Hamamatsu 432-8561, Japan

Academic Editor: Ruijun Zhao

Received: 08 October 2024 Revised: 20 February 2025 Accepted: 27 February 2025 Published: 12 March 2025

Control of infectious disease is very hard but important for the life of human beings. We study the susceptible–infected–susceptible (SIS) model of three-city networks. The SIS model simply contains both infection and recovery processes. We assume that human beings ("agents") live in three spatially separated cities, and they randomly migrate between cities. Two methods are applied: one is a computer simulation of an agent-based model, and the other is the theory of metapopulation dynamics. Both the simulation and theory reveal that the "hub city" plays an important role for disease control. It was found that we can eliminate the entire infection by disease control measures on the hub city only. Moreover, we found a paradoxical result: increased agent interaction does not necessarily lead to the spread of infection.
- lattice model,
- network,
- hub effect,
- SIS model,
- link
Citation: Nariyuki Nakagiri, Hiroki Yokoi, Yukio Sakisaka, Kei-ichi Tainaka, Kazunori Sato. Influence of network structure on infectious disease control[J]. Mathematical Biosciences and Engineering, 2025, 22(4): 943-961. doi: 10.3934/mbe.2025034

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Abstract

Control of infectious disease is very hard but important for the life of human beings. We study the susceptible–infected–susceptible (SIS) model of three-city networks. The SIS model simply contains both infection and recovery processes. We assume that human beings ("agents") live in three spatially separated cities, and they randomly migrate between cities. Two methods are applied: one is a computer simulation of an agent-based model, and the other is the theory of metapopulation dynamics. Both the simulation and theory reveal that the "hub city" plays an important role for disease control. It was found that we can eliminate the entire infection by disease control measures on the hub city only. Moreover, we found a paradoxical result: increased agent interaction does not necessarily lead to the spread of infection.

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