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人口接触对菌株竞争传播规模的影响
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Abstract:
为了研究人口接触模式对流行病传播的影响，本文基于经典的易感者–感染者–恢复者(SIR)模型，构建了一个包含接触强度的双菌株竞争传播模型，重点分析了接触强度对单菌株感染规模、双菌株感染规模及菌株间竞争的影响。结果表明，当接触强度达到一定阈值时，流行病的传播规模会迅速扩大；传播较快的菌株在高接触强度下占据竞争优势。此外，不同的菌株感染率对竞争态势的调节作用显著，反映了双菌株传播机制的复杂性。研究还表明，通过合理控制接触强度，可有效减缓流行病扩散速度并改变菌株间的竞争态势。本研究提出的模型为理解复杂传染病传播机制提供了新的理论框架，为制定精细化的防控策略提供了方法参考。
To investigate the impact of human contact patterns on epidemic transmission, this study extends the classical Susceptible-Infectious-Recovered (SIR) model by incorporating contact intensity into a dual-strain competitive transmission framework. The analysis focuses on the effects of contact intensity on the infection scale of single strains, the co-infection scale of dual strains, and the dynamics of strain competition. The results reveal that when contact intensity surpasses a certain threshold, the epidemic transmission scale expands rapidly. Strains with faster transmission rates gain a competitive advantage under high contact intensity. Furthermore, variations in strain-specific infection rates significantly influence the competitive dynamics, highlighting the complexity of dual-strain transmission mechanisms. The study also demonstrates that regulating contact intensity effectively slows down the spread of epidemics and alters the competitive dynamics between strains. The proposed model offers a novel theoretical framework for understanding the intricate mechanisms of infectious disease transmission and provides methodological insights for developing targeted and refined control strategies.
| [1] | Jiang, S. and Shi, Z. (2020) The First Disease X Is Caused by a Highly Transmissible Acute Respiratory Syndrome Coronavirus. Virologica Sinica, 35, 263-265. https://doi.org/10.1007/s12250-020-00206-5 |
| [2] | Yuan, X., Xue, Y. and Liu, M. (2013) Analysis of an Epidemic Model with Awareness Programs by Media on Complex Networks. Chaos, Solitons & Fractals, 48, 1-11. https://doi.org/10.1016/j.chaos.2012.12.001 |
| [3] | Wang, Y., Cao, J., Jin, Z., Zhang, H. and Sun, G. (2013) Impact of Media Coverage on Epidemic Spreading in Complex Networks. Physica A: Statistical Mechanics and Its Applications, 392, 5824-5835. https://doi.org/10.1016/j.physa.2013.07.067 |
| [4] | Hu, H., Nigmatulina, K. and Eckhoff, P. (2013) The Scaling of Contact Rates with Population Density for the Infectious Disease Models. Mathematical Biosciences, 244, 125-134. https://doi.org/10.1016/j.mbs.2013.04.013 |
| [5] | Ferguson, N.M., Cummings, D.A.T., Cauchemez, S., Fraser, C., Riley, S., Meeyai, A., et al. (2005) Strategies for Containing an Emerging Influenza Pandemic in Southeast Asia. Nature, 437, 209-214. https://doi.org/10.1038/nature04017 |
| [6] | Poletto, C., Meloni, S., Van Metre, A., Colizza, V., Moreno, Y. and Vespignani, A. (2015) Characterising Two-Pathogen Competition in Spatially Structured Environments. Scientific Reports, 5, Article No. 7895. https://doi.org/10.1038/srep07895 |
| [7] | Poletto, C., Meloni, S., Colizza, V., Moreno, Y. and Vespignani, A. (2013) Host Mobility Drives Pathogen Competition in Spatially Structured Populations. PLOS Computational Biology, 9, e1003169. https://doi.org/10.1371/journal.pcbi.1003169 |
| [8] | Colizza, V. and Vespignani, A. (2008) Epidemic Modeling in Metapopulation Systems with Heterogeneous Coupling Pattern: Theory and Simulations. Journal of Theoretical Biology, 251, 450-467. https://doi.org/10.1016/j.jtbi.2007.11.028 |
| [9] | Chang, S., Pierson, E., Koh, P.W., Gerardin, J., Redbird, B., Grusky, D., et al. (2020) Mobility Network Models of COVID-19 Explain Inequities and Inform Reopening. Nature, 589, 82-87. https://doi.org/10.1038/s41586-020-2923-3 |
| [10] | Li, R., Pei, S., Chen, B., Song, Y., Zhang, T., Yang, W., et al. (2020) Substantial Undocumented Infection Facilitates the Rapid Dissemination of Novel Coronavirus (SARS-CoV-2). Science, 368, 489-493. https://doi.org/10.1126/science.abb3221 |
| [11] | Dyson, L., Hill, E.M., Moore, S., Curran-Sebastian, J., Tildesley, M.J., Lythgoe, K.A., et al. (2021) Possible Future Waves of SARS-CoV-2 Infection Generated by Variants of Concern with a Range of Characteristics. Nature Communications, 12, Article No. 5730. https://doi.org/10.1038/s41467-021-25915-7 |
| [12] | Chen, J., Gu, C., Ruan, Z. and Tang, M. (2023) Competition of SARS-CoV-2 Variants on the Pandemic Transmission Dynamics. Chaos, Solitons & Fractals, 169, Article 113193. https://doi.org/10.1016/j.chaos.2023.113193 |
| [13] | de León, U.A., Avila-Vales, E. and Huang, K. (2022) Modeling COVID-19 Dynamic Using a Two-Strain Model with Vaccination. Chaos, Solitons & Fractals, 157, Article 111927. https://doi.org/10.1016/j.chaos.2022.111927 |
| [14] | Kermack, W.O. and McKendrick, A.G. (1927). A Contribution to the Mathematical Theory of Epidemics. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 115, 700-721. |
