Laboratoire de Physique de Clermont, CNRS/IN2P3, Université Clermont Auvergne, 63000, Clermont-Ferrand, France.
Institut Pascal, CHU Clermont-Ferrand, SIGMA Clermont, CNRS, Université Clermont Auvergne, 63000, Clermont-Ferrand, France.
Sci Rep. 2021 Dec 21;11(1):24326. doi: 10.1038/s41598-021-03812-9.
We develop a site-bond percolation model, called PERCOVID, in order to describe the time evolution of all epidemics propagating through respiratory tract or by skin contacts in human populations. This model is based on a network of social relationships representing interconnected households experiencing governmental non-pharmaceutical interventions. As a very first testing ground, we apply our model to the understanding of the dynamics of the COVID-19 pandemic in France from December 2019 up to December 2021. Our model shows the impact of lockdowns and curfews, as well as the influence of the progressive vaccination campaign in order to keep COVID-19 pandemic under the percolation threshold. We illustrate the role played by social interactions by comparing two typical scenarios with low or high strengths of social relationships as compared to France during the first wave in March 2020. We investigate finally the role played by the α and δ variants in the evolution of the epidemic in France till autumn 2021, paying particular attention to the essential role played by the vaccination. Our model predicts that the rise of the epidemic observed in July and August 2021 would not result in a new major epidemic wave in France.
我们开发了一种局域-键渗流模型，称为 PERCOVID，以描述通过呼吸道或皮肤接触在人群中传播的所有传染病的时间演化。该模型基于一个代表经历政府非药物干预的相互关联家庭的社交关系网络。作为一个非常初步的试验场，我们将模型应用于理解 2019 年 12 月至 2021 年 12 月期间法国 COVID-19 大流行的动态。我们的模型显示了封锁和宵禁的影响，以及逐步疫苗接种运动的影响，以将 COVID-19 大流行保持在渗流阈值以下。我们通过比较 2020 年 3 月第一波疫情期间法国社交关系强弱的两个典型场景，说明了社交互动的作用。最后，我们研究了 α 和 δ 变体在 2021 年秋季之前法国疫情演变中的作用，特别关注疫苗接种所起的重要作用。我们的模型预测，2021 年 7 月和 8 月观察到的疫情上升不会导致法国出现新的大流行浪潮。
