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Coronavirus Covid-19 spreading in Italy: optimizing an epidemiological model with dynamic social distancing through Differential Evolution
arXiv - CS - Social and Information Networks Pub Date : 2020-04-01 , DOI: arxiv-2004.00553
I. De Falco, A. Della Cioppa, U. Scafuri, and E. Tarantino

The aim of this paper consists in the application of a recent epidemiological model, namely SEIR with Social Distancing (SEIR--SD), extended here through the definition of a social distancing function varying over time, to assess the situation related to the spreading of the coronavirus Covid--19 in Italy and in two of its most important regions, i.e., Lombardy and Campania. To profitably use this model, the most suitable values of its parameters must be found. The estimation of the SEIR--SD model parameters takes place here through the use of Differential Evolution, a heuristic optimization technique. In this way, we are able to evaluate for each of the three above-mentioned scenarios the daily number of infectious cases from today until the end of virus spreading, the day(s) in which this number will be at its highest peak, and the day in which the infected cases will become very close to zero.

中文翻译:

冠状病毒 Covid-19 在意大利传播:通过差异进化优化具有动态社会距离的流行病学模型

本文的目的在于应用最近的流行病学模型,即 SEIR with Social Distancing (SEIR--SD),这里通过定义随时间变化的社会距离函数进行扩展,以评估与传播相关的情况冠状病毒 Covid-19 在意大利及其两个最重要的地区,即伦巴第和坎帕尼亚。为了有利地使用该模型,必须找到其参数的最合适值。SEIR--SD 模型参数的估计在此处通过使用差分进化(一种启发式优化技术)进行。通过这种方式,我们能够针对上述三种情况中的每一种评估从今天到病毒传播结束的每日感染病例数,该数字将达到最高峰值的那一天,
更新日期:2020-04-07
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