Modeling the effects of pandemics on physiology-related fertility decline in society.

IF 2.9
Frontiers in epidemiology Pub Date : 2026-09-16 eCollection Date: 2026-01-01 DOI:10.3389/fepid.2026.1740829
Teddy Lazebnik, Svetlana Bunimovich-Medrazitsky, Ariel Alexi
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Abstract

Pandemics throughout history have raised challenges in many forms, such as increased mortality rates, economic instability, and political shifts. Recent pandemics, coupled with globally declining fertility rates, pose unprecedented demographic challenges for humanity. A pandemic is inherently connected to a population's fertility in many ways - psychological, economic, and, most importantly, physiological. Nevertheless, this connection is mostly left unintended, blinding us to the effects of the pandemic-caused physiological fertility decline on the population's growth over time. In this study, we proposed a novel epidemiological model incorporating physiological fertility decline dynamics using an extended Susceptible-Infected-Recovered (SIR) model incorporating age groups, genders, birth and death dynamics, and infection-induced physiological fertility decline. Our model, based on real-world data from 10 large cities globally, demonstrates the impact of infection on fertility, which can persist for generations, creating demographic ripple effects that extend well beyond the immediate pandemic period. That said, the fertility drop is secondary to the pandemic spread, even for relatively high fertility decline due to the pathogen. These results have significant implications for public health policy and population planning. They highlight the need to integrate fertility considerations into pandemic preparedness strategies. Our study provides a quantitative framework for assessing the long-term demographic impacts of pandemics, offering policymakers tools to assess and potentially mitigate the impact of future disease outbreaks at the population level.

模拟流行病对社会中与生理有关的生育率下降的影响。
纵观历史,流行病带来了多种形式的挑战,如死亡率上升、经济不稳定和政治变化。最近的大流行病,加上全球生育率下降,给人类带来了前所未有的人口挑战。大流行在心理、经济以及最重要的生理等许多方面与人口的生育能力存在内在联系。然而,这种联系大多是无意的,使我们看不到流行病引起的生理生育率下降对人口增长的影响。在这项研究中,我们提出了一个新的流行病学模型,该模型采用了一个扩展的易感-感染-恢复(SIR)模型,该模型包含了年龄组、性别、出生和死亡动态以及感染引起的生理生育率下降。我们的模型基于来自全球10个大城市的真实数据,显示了感染对生育率的影响,这种影响可能持续几代人,产生的人口连锁反应远远超出了当前的大流行时期。也就是说,即使是由于病原体导致的生育率相对较高的下降,生育率的下降也是次要的。这些结果对公共卫生政策和人口规划具有重要意义。它们强调需要将生育方面的考虑纳入大流行防范战略。我们的研究为评估流行病对人口的长期影响提供了一个定量框架,为政策制定者提供了在人口层面评估和潜在地减轻未来疾病爆发影响的工具。
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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