The impact of heterogeneous recovery rates on traffic-driven epidemic spreading

Xing-Li Jing (), Jie Chen () and Yan-Qiang Li ()
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Xing-Li Jing: Shijiazhuang Tiedao University
Jie Chen: Anhui Normal University
Yan-Qiang Li: Shijiazhuang Tiedao University

The European Physical Journal B: Condensed Matter and Complex Systems, 2025, vol. 98, issue 11, 1-9

Abstract: Abstract Traffic-driven epidemic spreading has been widely studied, but the influence of heterogeneous recovery rates—common in real-world epidemic scenarios—has received limited attention. In this paper, we present a traffic-driven epidemic spreading model that incorporates heterogeneous recovery rates, reflecting the uneven distribution of medical resources in practical systems. We investigate how this heterogeneity impacts key epidemic dynamics, including the spreading speed, steady-state infection density, and epidemic threshold. The results demonstrate that nodal recovery heterogeneity significantly alters progression dynamics. Specifically, by strategically adjusting the distribution of recovery rates, the spread of the epidemic can be effectively controlled or even completely suppressed. These findings highlight the importance of considering recovery rate heterogeneity in epidemic modeling and offer valuable insights for optimizing epidemic prevention and control strategies in real-world traffic systems. Graphical abstract

Date: 2025
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DOI: 10.1140/epjb/s10051-025-01089-9

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