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Tracing day-zero and forecasting the COVID-19 outbreak in Lombardy, Italy: A compartmental modelling and numerical optimization approach

机译:追踪日零和预测伦巴第伦巴第型爆发,意大利:分区建模与数值优化方法

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Introduction Italy became the second epicenter of the novel coronavirus disease 2019 (COVID-19) pandemic after China, surpassing by far China’s death toll. The disease swept through Lombardy, which remained in lockdown for about two months, starting from the 8th of March. As of that day, the isolation measures taken in Lombardy were extended to the entire country. Here, assuming that effectively there was one case “zero” that introduced the virus to the region, we provide estimates for: (a) the day-zero of the outbreak in Lombardy, Italy; (b) the actual number of asymptomatic infected cases in the total population until March 8; (c) the basic ( R 0 )and the effective reproduction number ( R e ) based on the estimation of the actual number of infected cases. To demonstrate the efficiency of the model and approach, we also provide a tentative forecast two months ahead of time, i.e. until May 4, the date on which relaxation of the measures commenced, on the basis of the COVID-19 Community Mobility Reports released by Google on March 29.
机译:引言意大利成为2019年新型冠状病毒疾病的第二次震中(Covid-19)在中国之后的大流行,超越了远远超过中国的死亡人数。从3月8日开始,这种疾病席卷了伦巴第一次持续锁定约两个月。截至那一天,伦巴第采取的隔离措施延伸到整个国家。在这里,假设有效地存在一个“零”向该区域引入了病毒的一个例子,我们提供了估计:(a)意大利伦巴第爆发的日零; (b)总人口中的无症状感染病例的实际数量为3月8日; (c)基于估计受感染病例的实际数量的基本(R 0)和有效的再生数(R E)。为了展示模型和方法的效率,我们还提前两个月的预测,即在5月4日之前,措施开始放松的日期,即在释放的Covid-19社区移动性报告的基础上开始了谷歌3月29日。

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