Volume 1, Issue 1
Modelling the Effect of Human Heterogeneity on Infectious Disease Transmission Dynamics

Pengfei Song, Jianhong Wu & Yanni Xiao

CSIAM Trans. Life Sci., 1 (2025), pp. 1-21.

Published online: 2025-03

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  • Abstract

Human heterogeneity is a critical issue in infectious disease transmission dynamics modelling, and it has recently received much attention in COVID-19 studies. In this article, a general human heterogeneous disease model with mutation is proposed to comprehensively study the effects of human heterogeneity on basic reproduction number, final epidemic size and herd immunity. We show that human heterogeneity may increase or decrease herd immunity level, strongly depending on some convexity of the heterogeneity function, which gives new insights and extends the results in [Britton et al., Science, 369: 846–849, 2020]. Moreover, human heterogeneity may decrease the basic reproduction number but increase the level of herd immunity, implying the unreliability of the basic reproduction number in characterizing the spread and control of infectious diseases with human heterogeneity.

  • AMS Subject Headings

35J55, 35B32

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COPYRIGHT: © Global Science Press

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@Article{CSIAM-LS-1-1, author = {Song , PengfeiWu , Jianhong and Xiao , Yanni}, title = {Modelling the Effect of Human Heterogeneity on Infectious Disease Transmission Dynamics}, journal = {CSIAM Transactions on Life Sciences}, year = {2025}, volume = {1}, number = {1}, pages = {1--21}, abstract = {

Human heterogeneity is a critical issue in infectious disease transmission dynamics modelling, and it has recently received much attention in COVID-19 studies. In this article, a general human heterogeneous disease model with mutation is proposed to comprehensively study the effects of human heterogeneity on basic reproduction number, final epidemic size and herd immunity. We show that human heterogeneity may increase or decrease herd immunity level, strongly depending on some convexity of the heterogeneity function, which gives new insights and extends the results in [Britton et al., Science, 369: 846–849, 2020]. Moreover, human heterogeneity may decrease the basic reproduction number but increase the level of herd immunity, implying the unreliability of the basic reproduction number in characterizing the spread and control of infectious diseases with human heterogeneity.

}, issn = {3006-2721}, doi = {https://doi.org/10.4208/csiam-ls.SO-2024-0001}, url = {http://global-sci.org/intro/article_detail/csiam-ls/23908.html} }
TY - JOUR T1 - Modelling the Effect of Human Heterogeneity on Infectious Disease Transmission Dynamics AU - Song , Pengfei AU - Wu , Jianhong AU - Xiao , Yanni JO - CSIAM Transactions on Life Sciences VL - 1 SP - 1 EP - 21 PY - 2025 DA - 2025/03 SN - 1 DO - http://doi.org/10.4208/csiam-ls.SO-2024-0001 UR - https://global-sci.org/intro/article_detail/csiam-ls/23908.html KW - SEIR model, human heterogeneity, basic reproduction number, herd immunity level, final epidemic size. AB -

Human heterogeneity is a critical issue in infectious disease transmission dynamics modelling, and it has recently received much attention in COVID-19 studies. In this article, a general human heterogeneous disease model with mutation is proposed to comprehensively study the effects of human heterogeneity on basic reproduction number, final epidemic size and herd immunity. We show that human heterogeneity may increase or decrease herd immunity level, strongly depending on some convexity of the heterogeneity function, which gives new insights and extends the results in [Britton et al., Science, 369: 846–849, 2020]. Moreover, human heterogeneity may decrease the basic reproduction number but increase the level of herd immunity, implying the unreliability of the basic reproduction number in characterizing the spread and control of infectious diseases with human heterogeneity.

Song , PengfeiWu , Jianhong and Xiao , Yanni. (2025). Modelling the Effect of Human Heterogeneity on Infectious Disease Transmission Dynamics. CSIAM Transactions on Life Sciences. 1 (1). 1-21. doi:10.4208/csiam-ls.SO-2024-0001
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