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多波大流行与多期/多相流行:COVID-19 大流行的全球形势。

Multiple pandemic waves vs multi-period/multi-phasic epidemics: Global shape of the COVID-19 pandemic.

机构信息

Dipartimento di Matematica e Geoscienze, Universitá di Trieste, Via Alfonso Valerio 12, Edificio H2bis, 34127 Trieste, Italy.

Mathematics Department, University of Trento, Via Sommarive 14, 38123 Trento, Italy.

出版信息

J Theor Biol. 2024 Oct 7;593:111881. doi: 10.1016/j.jtbi.2024.111881. Epub 2024 Jul 5.

DOI:10.1016/j.jtbi.2024.111881
PMID:38972568
Abstract

The overall course of the COVID-19 pandemic in Western countries has been characterized by complex sequences of phases. In the period before the arrival of vaccines, these phases were mainly due to the alternation between the strengthening/lifting of social distancing measures, with the aim to balance the protection of health and that of the society as a whole. After the arrival of vaccines, this multi-phasic character was further emphasized by the complicated deployment of vaccination campaigns and the onset of virus' variants. To cope with this multi-phasic character, we propose a theoretical approach to the modeling of overall pandemic courses, that we term multi-period/multi-phasic, based on a specific definition of phase. This allows a unified and parsimonious representation of complex epidemic courses even when vaccination and virus' variants are considered, through sequences of weak ergodic renewal equations that become fully ergodic when appropriate conditions are met. Specific hypotheses on epidemiological and intervention parameters allow reduction to simple models. The framework suggest a simple, theory driven, approach to data explanation that allows an accurate reproduction of the overall course of the COVID-19 epidemic in Italy since its beginning (February 2020) up to omicron onset, confirming the validity of the concept.

摘要

在西方国家,COVID-19 大流行的总体进程以复杂的阶段序列为特征。在疫苗到来之前,这些阶段主要是由于社会隔离措施的加强/放宽交替进行,目的是平衡保护健康和保护整个社会。疫苗接种运动的复杂部署和病毒变异的出现进一步强调了这种多阶段特征。为了应对这种多阶段特征,我们提出了一种整体大流行进程建模的理论方法,我们称之为多周期/多阶段,基于阶段的特定定义。这允许通过弱遍历更新方程的序列来统一和简洁地表示复杂的流行过程,即使考虑到疫苗接种和病毒变异,这些方程在满足适当条件时变为完全遍历。关于流行病学和干预参数的具体假设允许简化为简单的模型。该框架提出了一种简单的、基于理论的数据分析方法,可以准确再现意大利 COVID-19 疫情自 2020 年 2 月开始爆发至奥密克戎出现的全过程,验证了该概念的有效性。

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