Parolini Nicola, Dede' Luca, Ardenghi Giovanni, Quarteroni Alfio
MOX, Department of Mathematics, Politecnico di Milano, Italy.
Institute of Mathematics, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
Infect Dis Model. 2022 Jun;7(2):45-63. doi: 10.1016/j.idm.2022.03.002. Epub 2022 Mar 9.
Several epidemiological models have been proposed to study the evolution of COVID-19 pandemic. In this paper, we propose an extension of the SUIHTER model, to analyse the COVID-19 spreading in Italy, which accounts for the vaccination campaign and the presence of new variants when they become dominant. In particular, the specific features of the variants (e.g. their increased transmission rate) and vaccines (e.g. their efficacy to prevent transmission, hospitalization and death) are modeled, based on clinical evidence. The new model is validated comparing its near-future forecast capabilities with other epidemiological models and exploring different scenario analyses.
已经提出了几种流行病学模型来研究新冠疫情的演变。在本文中,我们提出了SUIHTER模型的一个扩展,以分析新冠病毒在意大利的传播情况,该扩展模型考虑了疫苗接种运动以及新变种成为主导时的情况。特别是,基于临床证据对变种的具体特征(例如其增加的传播率)和疫苗(例如其预防传播、住院和死亡的效力)进行了建模。通过将其近期预测能力与其他流行病学模型进行比较并探索不同的情景分析,对新模型进行了验证。