Modelling and predicting the effect of social distancing and travel restrictions on COVID-19 spreading.
Modelling and predicting the effect of social distancing and travel restrictions on COVID-19 spreading.
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建模和预测社交距离和旅行限制对COVID-19传播的影响。
DOI：
10.1098/rsif.2020.0875
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发表时间：
2021-03
期刊：
影响因子：
--
通讯作者：
Rizzo A
中科院分区：
文献类型：
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作者：
Parino F;Zino L;Porfiri M;Rizzo A
迄今为止，应对新冠肺炎疫情蔓延的唯一有效手段是非药物干预，这需要采取减少社会活动和行动限制的政策。量化它们的影响很困难，但这是减少它们的社会和经济后果的关键。在这里，我们介绍了一个基于时间网络的元人口模型，该模型基于意大利新冠肺炎疫情数据进行校准，并应用于评估这两种类型的NPI的结果。我们的方法结合了元人口模型的粒度空间建模的优势和通过活动驱动的网络现实地描述社会联系的能力。我们专注于理清这两种不同类型的NPI的影响：旨在减少个人社交活动的NPI，例如通过封锁，以及那些强制实施流动限制的NPI。我们提供了一个有价值的框架来评估不同的NPI的有效性，这些NPI的时机和严重性各不相同。结果表明，行动限制的效果在很大程度上取决于在疫情爆发的早期阶段及时实施非营利机构的可能性，而减少活动的政策应在之后优先考虑。
To date, the only effective means to respond to the spreading of the COVID-19 pandemic are non-pharmaceutical interventions (NPIs), which entail policies to reduce social activity and mobility restrictions. Quantifying their effect is difficult, but it is key to reducing their social and economic consequences. Here, we introduce a meta-population model based on temporal networks, calibrated on the COVID-19 outbreak data in Italy and applied to evaluate the outcomes of these two types of NPIs. Our approach combines the advantages of granular spatial modelling of meta-population models with the ability to realistically describe social contacts via activity-driven networks. We focus on disentangling the impact of these two different types of NPIs: those aiming at reducing individuals’ social activity, for instance through lockdowns, and those that enforce mobility restrictions. We provide a valuable framework to assess the effectiveness of different NPIs, varying with respect to their timing and severity. Results suggest that the effects of mobility restrictions largely depend on the possibility of implementing timely NPIs in the early phases of the outbreak, whereas activity reduction policies should be prioritized afterwards.