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免疫动力学如何塑造多季节流行:一维抗原空间中的连续离散模型。

How immune dynamics shape multi-season epidemics: a continuous-discrete model in one dimensional antigenic space.

机构信息

New Zealand Institute for Advanced Study and the Infectious Disease Research Centre, Massey University, Auckland, New Zealand.

Health and Biosecurity, CSIRO, Townsville, QLD, 4814, Australia.

出版信息

J Math Biol. 2024 Mar 27;88(4):48. doi: 10.1007/s00285-024-02076-x.

Abstract

We extend a previously published model for the dynamics of a single strain of an influenza-like infection. The model incorporates a waning acquired immunity to infection and punctuated antigenic drift of the virus, employing a set of coupled integral equations within a season and a discrete map between seasons. The long term behaviour of the model is demonstrated by examples where immunity to infection depends on the time since a host was last infected, and where immunity depends on the number of times that a host has been infected. The first scenario leads to complicated dynamics in some regions of parameter space, and to regions of parameter space with more than one attractor. The second scenario leads to a stable fixed point, corresponding to an identical epidemic each season. We also examine the model with both paradigms in combination, almost always but not exclusively observing a stable fixed point or periodic solution. Adding stochastic perturbations to the between season map fails to destroy the model's qualitative dynamics. Our results suggest that if the level of host immunity depends on the elapsed time since the last infection then the epidemiological dynamics may be unpredictable.

摘要

我们扩展了之前发表的一个流感样感染单株动力学模型。该模型结合了感染获得性免疫的衰减和病毒的间断抗原漂移,在一个季节内采用一组耦合积分方程和季节之间的离散映射。通过一些例子展示了模型的长期行为,其中感染免疫力取决于宿主上次感染的时间,以及宿主感染的次数。第一种情况导致在某些参数空间区域出现复杂的动力学,以及具有多个吸引子的参数空间区域。第二种情况导致稳定的固定点,对应于每个季节相同的传染病。我们还研究了两种情况的组合模型,几乎总是但不是排他性地观察到稳定的固定点或周期解。对季节间映射添加随机扰动未能破坏模型的定性动力学。我们的结果表明,如果宿主免疫力水平取决于上次感染以来的时间,那么流行病学动态可能是不可预测的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2527/10973021/b17a60aba6ea/285_2024_2076_Fig1_HTML.jpg

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