A Dual-age Structured Epidemiological Model with Waning Immunity and Reinfection.

IF 2.3 4区 数学 Q2 BIOLOGY
Raimund M Kovacevic, Nikolaos I Stilianakis, Vladimir M Veliov
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Abstract

Waning immunity and reinfection are critical features of many infectious diseases, but epidemiological models often fail to capture the interaction between an individual's immunity history and their current infection status, or do so only simplistically. We develop a dual-age structured model tracking immunity age (time since last recovery) and infection age (time since infection) to analyze epidemic dynamics under waning immunity and reinfection. The model is formulated as a system of age-structured partial differential equations describing susceptible and infected populations stratified by both age variables. The contact rate, mortality and recovery rates, susceptibility, and pathogen load are all treated as parameter functions depending on both immunity and infection age. We derive basic reproduction numbers and numerically solve the system using a second-order Runge-Kutta scheme along characteristic lines. We further extend the model to treat vaccination interventions, specifically booster vaccination strategies targeting individuals by immunity age - interventions that cannot be formulated in standard models. Numerical results reveal that higher contact rates produce larger oscillation amplitudes with longer inter-epidemic periods. However, long-term oscillation amplitude and cumulative infections depend non-monotonically on the initial infected population size, indicating that the relationship between initial infection levels and long-term epidemic outcomes is not straightforward. Vaccination efficiency depends critically on the pathogen load profile, with more concentrated distributions requiring higher vaccination rates for elimination. Most efficient strategies target intermediate immunity ages rather than only fully waned individuals.

具有免疫减弱和再感染的双年龄结构流行病学模型。
免疫力下降和再感染是许多传染病的重要特征,但流行病学模型往往无法捕捉到个体免疫史与其当前感染状态之间的相互作用,或者只是简单地这样做。我们建立了一个双年龄结构模型,跟踪免疫年龄(自上次恢复以来的时间)和感染年龄(自感染以来的时间),以分析免疫力下降和再次感染时的流行动态。该模型被表述为一个年龄结构的偏微分方程系统,描述了易感人群和受感染人群的年龄变量分层。接触率、死亡率和恢复率、易感性和病原体负荷均作为参数函数处理,取决于免疫和感染年龄。导出了基本的再现数,并利用二阶龙格-库塔格式沿特征线对系统进行了数值求解。我们进一步扩展该模型来治疗疫苗接种干预措施,特别是通过免疫年龄针对个体的加强疫苗接种策略-无法在标准模型中制定的干预措施。数值结果表明,较高的接触率会产生较大的振荡幅度和较长的流行周期。然而,长期振荡振幅和累积感染非单调地依赖于初始感染人群的大小,这表明初始感染水平与长期流行结果之间的关系并不直接。疫苗接种效率在很大程度上取决于病原体负荷情况,分布越集中,需要更高的疫苗接种率才能消除。最有效的策略针对的是中间免疫年龄,而不仅仅是完全衰弱的个体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.90
自引率
8.60%
发文量
123
审稿时长
7.5 months
期刊介绍: The Bulletin of Mathematical Biology, the official journal of the Society for Mathematical Biology, disseminates original research findings and other information relevant to the interface of biology and the mathematical sciences. Contributions should have relevance to both fields. In order to accommodate the broad scope of new developments, the journal accepts a variety of contributions, including: Original research articles focused on new biological insights gained with the help of tools from the mathematical sciences or new mathematical tools and methods with demonstrated applicability to biological investigations Research in mathematical biology education Reviews Commentaries Perspectives, and contributions that discuss issues important to the profession All contributions are peer-reviewed.
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