Abstract
Communities are commonly not isolated but interact asymmetrically with each other, allowing the propagation of infectious diseases within the same community and between different communities. To reveal the impact of asymmetrical interactions and contact heterogeneity on disease transmission, we formulate a two-community SIR epidemic model, in which each community has its contact structure while communication between communities occurs through temporary commuters. We derive an explicit formula for the basic reproduction number \({\mathcal {R}}_0\), give an implicit equation for the final epidemic size z, and analyze the relationship between them. Unlike the typical positive correlation between \({\mathcal {R}}_0\) and z in the classic SIR model, we find a negatively correlated relationship between counterparts of our model deviating from homogeneous populations. Moreover, we investigate the impact of asymmetric coupling mechanisms on \({\mathcal {R}}_0\). The results suggest that, in scenarios with restricted movement of susceptible individuals within a community, \({\mathcal {R}}_0\) does not follow a simple monotonous relationship, indicating that an unbending decrease in the movement of susceptible individuals may increase \({\mathcal {R}}_0\). We further demonstrate that network contacts within communities have a greater effect on \({\mathcal {R}}_0\) than casual contacts between communities. Finally, we develop an epidemic model without restriction on the movement of susceptible individuals, and the numerical simulations suggest that the increase in human flow between communities leads to a larger \({\mathcal {R}}_0\).
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Acknowledgements
Yi Wang’s research is partially supported by the National Natural Science Foundation of China under Grants 12171443 and 11801532, and the Fundamental Research Funds for the Central Universities under Grant G1323523061. Guiquan Sun’s research is partially supported by the National Natural Science Foundation of China under Grants 12022113 and 12271314. Hao Wang’s research is partially supported by the Natural Sciences and Engineering Research Council of Canada under Discovery Grant RGPIN-2020-03911 and Accelerator Supplement Award RGPAS-2020-00090. The authors thank the handling editor and the two anonymous referees for helpful comments and suggestions.
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Appendix
Appendix
We can obtain the roots of the quaternion equation (3.10) using the Ferrari’s solution (see, https://en.wikipedia.org/wiki/Quartic_function#Ferraris_solution for the exact solution procedure):
where
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Han, Z., Wang, Y., Gao, S. et al. Final epidemic size of a two-community SIR model with asymmetric coupling. J. Math. Biol. 88, 51 (2024). https://doi.org/10.1007/s00285-024-02073-0
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DOI: https://doi.org/10.1007/s00285-024-02073-0