Riding the waves from epidemic to endemic: Viral mutations, immunological change and policy responses

IF 1.2 4区 生物学 Q4 ECOLOGY
D. Grass , S. Wrzaczek , J.P. Caulkins , G. Feichtinger , R.F. Hartl , P.M. Kort , M. Kuhn , A. Prskawetz , M. Sanchez-Romero , A. Seidl
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引用次数: 0

Abstract

Nonpharmaceutical interventions (NPI) are an important tool for countering pandemics such as COVID-19. Some are cheap; others disrupt economic, educational, and social activity. The latter force governments to balance the health benefits of reduced infection and death against broader lockdown-induced societal costs. A literature has developed modeling how to optimally adjust lockdown intensity as an epidemic evolves. This paper extends that literature by augmenting the classic SIR model with additional states and flows capturing decay over time in vaccine-conferred immunity, the possibility that mutations create variants that erode immunity, and that protection against infection erodes faster than protecting against severe illness. As in past models, we find that small changes in parameter values can tip the optimal response between very different solutions, but the extensions considered here create new types of solutions. In some instances, it can be optimal to incur perpetual epidemic waves even if the uncontrolled infection prevalence would settle down to a stable intermediate level.

从流行病到地方病,乘风破浪:病毒变异、免疫学变化和对策
非药物干预(NPI)是应对 COVID-19 等流行病的重要工具。有些干预措施成本低廉,有些则会破坏经济、教育和社会活动。后者迫使政府在减少感染和死亡带来的健康益处与更广泛的封锁引起的社会成本之间进行权衡。已有文献对如何随着疫情的发展以最佳方式调整封锁强度进行了建模。本文对这一文献进行了扩展,在经典的 SIR 模型的基础上增加了捕捉疫苗免疫力随时间衰减的状态和流量、突变产生侵蚀免疫力的变种的可能性,以及预防感染比预防重症侵蚀得更快的可能性。与过去的模型一样,我们发现参数值的微小变化就能使最优反应在截然不同的解决方案之间产生偏差,但本文所考虑的扩展会产生新类型的解决方案。在某些情况下,即使不受控制的感染率会下降到一个稳定的中间水平,但引发持续的流行病浪潮也可能是最佳选择。
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
Theoretical Population Biology
Theoretical Population Biology 生物-进化生物学
CiteScore
2.50
自引率
14.30%
发文量
43
审稿时长
6-12 weeks
期刊介绍: An interdisciplinary journal, Theoretical Population Biology presents articles on theoretical aspects of the biology of populations, particularly in the areas of demography, ecology, epidemiology, evolution, and genetics. Emphasis is on the development of mathematical theory and models that enhance the understanding of biological phenomena. Articles highlight the motivation and significance of the work for advancing progress in biology, relying on a substantial mathematical effort to obtain biological insight. The journal also presents empirical results and computational and statistical methods directly impinging on theoretical problems in population biology.
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