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Analysis and forecast of COVID-19 spreading in China, Italy and France

机译:中国,意大利和法国Covid-19蔓延的分析与预测

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In this note we analyze the temporal dynamics of the coronavirus disease 2019 outbreak in China, Italy and France in the time window 22/01 - 15/03/2020. A first analysis of simple day-lag maps points to some universality in the epidemic spreading, suggesting that simple mean-field models can be meaningfully used to gather a quantitative picture of the epidemic spreading, and notably the height and time of the peak of confirmed infected individuals. The analysis of the same data within a simple susceptible-infected-recovered-deaths model indicates that the kinetic parameter that describes the rate of recovery seems to be the same, irrespective of the country, while the infection and death rates appear to be more variable. The model places the peak in Italy around March 21st 2020, with a peak number of infected individuals of about 260 00 (not including recovered and dead) and a number of deaths at the end of the epidemics of about 18,000. Since the confirmed cases are believed to be between 10 and 20% of the real number of individuals who eventually get infected, the apparent mortality rate of COVID-19 falls between 4% and 8% in Italy, while it appears substantially lower, between 1% and 3% in China. Based on our calculations, we estimate that 2500 ventilation units should represent a fair figure for the peak requirement to be considered by health authorities in Italy for their strategic planning. Finally, a simulation of the effects of drastic containment measures on the outbreak in Italy indicates that a reduction of the infection rate indeed causes a quench of the epidemic peak. However, it is also seen that the infection rate needs to be cut down drastically and quickly to observe an appreciable decrease of the epidemic peak and mortality rate. This appears only possible through a concerted and disciplined, albeit painful, effort of the population as a whole. (C) 2020 Elsevier Ltd. All rights reserved.
机译:在本说明书中,我们分析了2019年中国,意大利和法国的冠状病毒疾病的时间动态在时间窗口22/01 - 15/03/03/03/03/03/03/03/03。对简单的日滞地图的第一次分析在疫情扩展中指出了一些普遍性,表明简单的平均场模型可以有意义地用于收集疫情传播的定量图片,并且特别是确认峰值的高度和时间受感染的个体。在简单的敏感感染回收死亡模型中对相同数据的分析表明,该国家的恢复速率的动力学参数似乎是相同的,而不管该国似乎都是相同的,而感染和死亡率似乎变得更加可变。该模型将于3月21日左右的意大利达到了意大利,峰值数量约为260 00(不包括恢复和死亡),并在该流行病结束时的死亡人数约为18,000。由于确认的案件据信,占最终被感染的真实人数的10%至20%,COVID-19的表观死亡率在意大利的4%和8%之间跌至4%至8%之间,而在1之间出现显着降低中国%和3%。根据我们的计算,我们估计2500通风单位应该代表意大利卫生当局考虑的最高要求的公平形象,以获得其战略规划。最后,模拟了激增措施对意大利爆发的效果表明感染率的降低确实导致淬火流行峰。然而,还可以看出,感染率需要大幅度和快速地削减,观察疫情峰值和死亡率的明显降低。这似乎只有通过一点纪律,尽管痛苦,但整个人口努力。 (c)2020 elestvier有限公司保留所有权利。

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