Given the severe impact of COVID-19 on several societal levels, it is of crucial importance to model the impact of restriction measures on the pandemic evolution, so that governments are able to take informed decisions. Even though there have been countless attempts to propose diverse models since the raise of the outbreak, the increase in data availability and start of vaccination campaigns calls for updated models and studies. Furthermore, most of the works are focused on a very particular place or application and we strive to attain a more general model, resorting to data from different countries. In particular, we compare Great Britain and Israel, two highly different scenarios in terms of vaccination plans and social structure. We build a network-based model, complex enough to model different scenarios of government-mandated restrictions, but generic enough to be applied to any population. To ease the computational load we propose a decomposition strategy for our model.
翻译:鉴于COVID-19对若干社会层面的严重影响,必须模拟限制措施对流行病演变的影响,以便各国政府能够作出知情的决定,尽管自爆发以来,人们曾无数次试图提出各种模式,但数据提供量的增加和疫苗接种运动的开始都要求更新模式和研究,此外,大多数工作都集中在一个非常特殊的地方或应用上,我们努力利用不同国家的数据,形成一个更普遍的模型,特别是,我们比较英国和以色列,在疫苗接种计划和社会结构方面存在着两种截然不同的情景。我们建立了一个基于网络的模型,这个模型非常复杂,足以模拟政府授权的限制的不同情景,但具有通用性,足以适用于任何人口。为了减轻计算负担,我们提出了我们模型的分解战略。