Mari Lorenzo, Casagrandi Renato, Bertuzzo Enrico, Pasetto Damiano, Miccoli Stefano, Rinaldo Andrea, Gatto Marino
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.
Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca' Foscari Venezia, Venice, Italy.
Nat Commun. 2021 May 12;12(1):2752. doi: 10.1038/s41467-021-22878-7.
Several indices can predict the long-term fate of emerging infectious diseases and the effect of their containment measures, including a variety of reproduction numbers (e.g. [Formula: see text]). Other indices evaluate the potential for transient increases of epidemics eventually doomed to disappearance, based on generalized reactivity analysis. They identify conditions for perturbations to a stable disease-free equilibrium ([Formula: see text]) to grow, possibly causing significant damage. Here, we introduce the epidemicity index e, a threshold-type indicator: if e > 0, initial foci may cause infection peaks even if [Formula: see text]. Therefore, effective containment measures should achieve a negative epidemicity index. We use spatially explicit models to rank containment measures for projected evolutions of the ongoing pandemic in Italy. There, we show that, while the effective reproduction number was below one for a sizable timespan, epidemicity remained positive, allowing recurrent infection flare-ups well before the major epidemic rebounding observed in the fall.
有几个指标可以预测新发传染病的长期发展趋势及其防控措施的效果，包括各种繁殖数（例如[公式：见正文]）。其他指标基于广义反应性分析，评估最终注定会消失的疫情短暂增加的可能性。它们确定了稳定的无病平衡（[公式：见正文]）受到扰动而增长的条件，这可能会造成重大损害。在此，我们引入流行指数e，这是一个阈值型指标：如果e > 0，即使[公式：见正文]，初始疫源地也可能导致感染高峰。因此，有效的防控措施应实现负流行指数。我们使用空间明确模型对意大利当前大流行的预测演变中的防控措施进行排名。在那里，我们表明，虽然有效繁殖数在相当长的一段时间内低于1，但流行指数仍为正值，使得在秋季观察到的主要疫情反弹之前就出现了反复的感染激增。
