Bertuzzo Enrico, Mari Lorenzo, Pasetto Damiano, Miccoli Stefano, Casagrandi Renato, Gatto Marino, Rinaldo Andrea
Dipartimento di Scienze Ambientali, Informatica e Statistica, Universitá Ca' Foscari Venezia, 30172, Venezia-Mestre, IT, Italy.
Science of Complexity Research Unit, European Centre for Living Technology, 30123, Venice, IT, Italy.
Nat Commun. 2020 Aug 26;11(1):4264. doi: 10.1038/s41467-020-18050-2.
The pressing need to restart socioeconomic activities locked-down to control the spread of SARS-CoV-2 in Italy must be coupled with effective methodologies to selectively relax containment measures. Here we employ a spatially explicit model, properly attentive to the role of inapparent infections, capable of: estimating the expected unfolding of the outbreak under continuous lockdown (baseline trajectory); assessing deviations from the baseline, should lockdown relaxations result in increased disease transmission; calculating the isolation effort required to prevent a resurgence of the outbreak. A 40% increase in effective transmission would yield a rebound of infections. A control effort capable of isolating daily ~5.5% of the exposed and highly infectious individuals proves necessary to maintain the epidemic curve onto the decreasing baseline trajectory. We finally provide an ex-post assessment based on the epidemiological data that became available after the initial analysis and estimate the actual disease transmission that occurred after weakening the lockdown.
在意大利,重启因防控新冠病毒传播而封锁的社会经济活动的迫切需求,必须与有选择性放松防控措施的有效方法相结合。在此,我们采用一个空间明确的模型,充分考虑隐性感染的作用,该模型能够:估计在持续封锁下疫情的预期发展(基线轨迹);评估若放松封锁导致疾病传播增加时与基线的偏差;计算防止疫情反弹所需的隔离力度。有效传播率增加40%将导致感染反弹。事实证明,每天隔离约5.5%的暴露且具有高传染性的个体的防控力度,对于维持疫情曲线沿下降的基线轨迹发展是必要的。我们最后根据初始分析后可获取的流行病学数据进行事后评估,并估计放松封锁后实际发生的疾病传播情况。