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A statistical analysis of the novel coronavirus (COVID-19) in Italy and Spain

机译:意大利和西班牙新型冠状病毒(Covid-19)的统计分析

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The novel coronavirus (COVID-19) that was first reported at the end of 2019 has impacted almost every aspect of life as we know it. This paper focuses on the incidence of the disease in Italy and Spain—two of the first and most affected European countries. Using two simple mathematical epidemiological models—the Susceptible-Infectious-Recovered model and the log-linear regression model, we model the daily and cumulative incidence of COVID-19 in the two countries during the early stage of the outbreak, and compute estimates for basic measures of the infectiousness of the disease including the basic reproduction number, growth rate, and doubling time. Estimates of the basic reproduction number were found to be larger than 1 in both countries, with values being between 2 and 3 for Italy, and 2.5 and 4 for Spain. Estimates were also computed for the more dynamic effective reproduction number, which showed that since the first cases were confirmed in the respective countries the severity has generally been decreasing. The predictive ability of the log-linear regression model was found to give a better fit and simple estimates of the daily incidence for both countries were computed.
机译:2019年底首次报道的新型冠状病毒(Covid-19)已经影响了我们所知道的几乎所有方面。本文重点介绍了意大利和西班牙的疾病的发病率和最受影响最多的欧洲国家的疾病。使用两种简单的数学流行病学模型 - 敏感传染性恢复的模型和对数线性回归模型,我们在爆发的早期阶段模拟了两国Covid-19的日常和累积发生率,并计算了基本的估计疾病传染病的措施,包括基本的再生数,增长率和倍增时间。发现基本再现数量的估计在两个国家/地区的1个大于1,意大利的值为2和3,2.5和4个用于西班牙。对于更具动态的有效再现号码,估计数也被计算出现,因为自第一个案件在各个国家确认,严重程度一般一直在下降。发现了对数线性回归模型的预测能力,为计算了两个国家的日常发病率的更好的拟合和简单估计。

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