Cheng Tianyu, Zou Xingfu
Department of Mathematics, University of Western Ontario, London, ON, N6A 5B7, Canada.
J Math Biol. 2025 Jul 22;91(2):19. doi: 10.1007/s00285-025-02249-2.
In this paper, we use the renewal equation approach to explore the impact of behaviour change and/or non-pharmaceutical interventions (NPIs) on the final size and peak size of an infectious disease without demography. To this end, we derive the renewal equations (REs) for the force of infection (both instantaneous and cumulative) that have reflected the NPIs and/or behaviour change by the notion of practically susceptible population. A novelty in these REs is that they contain time-varying kernels arising from the incorporation of effect of behaviour change. We then build the new REs into the Kermack-McKendrick model to obtain a general full model. Following Breda et al. (J Biol Dyn 6(sup2):103-117, 2012) and Diekmann et al. (Proc Natl Acad Sci USA 118(39):e2106332118, 2021), we analyze this new model to derive a general formula for the final size relation, by which we find that the final size relation depends not only on the basic reproduction number [Formula: see text] but also on other associated values that reflect the impact of behaviour change. Specifically, we demonstrate that behaviour change can reduce the infection peak and herd immunity threshold in some specific models.
在本文中,我们使用更新方程方法来探究行为改变和/或非药物干预措施(NPIs)对无人口统计学因素的传染病最终规模和峰值规模的影响。为此,我们推导了感染率(瞬时感染率和累积感染率)的更新方程(REs),这些方程通过实际易感人群的概念反映了NPIs和/或行为改变。这些更新方程的一个新颖之处在于它们包含了因纳入行为改变效应而产生的时变核。然后,我们将新的更新方程纳入Kermack-McKendrick模型,以获得一个通用的完整模型。按照Breda等人(《生物动力学杂志》6(增刊2):103 - 117,2012年)以及Diekmann等人(《美国国家科学院院刊》118(39):e2106332118,2021年)的方法,我们对这个新模型进行分析,以推导出最终规模关系的通用公式,通过该公式我们发现最终规模关系不仅取决于基本再生数[公式:见正文],还取决于其他反映行为改变影响的相关值。具体而言,我们证明了在某些特定模型中,行为改变可以降低感染峰值和群体免疫阈值。