Predicting the ultimate outcome of the COVID-19 outbreak in Italy

arxiv(2020)

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摘要
During the COVID-19 outbreak, it is essential to monitor the effectiveness of measures taken by governments on the course of the epidemic. Here we show that there is already a sufficient amount of data collected in Italy to predict the outcome of the process. We show that using the proper metric, the data from Hubei Province and Italy has striking similarity, which enables us to calculate the expected number of confirmed cases and the number of deaths by the end of the process. Our predictions will improve as new data points are generated day by day, which can help to make further public decisions. The method is based on the data analysis of logistic growth equations describing the process on the macroscopic level. At the time of writing, the number of fatalities in Italy is expected to be 6000, and the crisis ends before April 15, 2020.
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