论文标题
Arima预测在意大利，俄罗斯和美国的Covid-19发病率
ARIMA forecasting of COVID-19 incidence in Italy, Russia, and the USA
论文作者
论文摘要
新型冠状病毒病（COVID-19）是一种严重的呼吸道感染，2019年12月在中国武汉正式发生。2月下旬，该疾病开始迅速蔓延到世界各地，导致严重的健康，社会和经济紧急情况。本文旨在通过自动回归综合运动平均平均模型（ARIMA）模型（应用于意大利，俄罗斯，俄罗斯和美国）对Covid-19-19的流行媒介的短期到中期发生率进行，该分析是对新日常确认的COVID-19案例的数量进行的，该案例由世界计网站收集。最好的Arima模型是意大利（4,2,4），俄罗斯（1,2,1）和美国（6,2,3）。结果表明：i）当新的日常病例开始稳定时，Arima模型足够可靠； ii）意大利，美国和俄罗斯分别在4月中旬，五月中旬和5月下旬达到了199日的Covid-19峰； iii）俄罗斯和美国将需要比意大利更多的时间将Covid-19案件接近零。这可能表明采用快速有效的锁定措施的应用，这在意大利相对更严格。因此，即使应该谨慎解释结果，Arima模型似乎也是一个很好的工具，可以帮助卫生当局监测暴发的扩散。
The novel Coronavirus disease (COVID-19) is a severe respiratory infection that officially occurred in Wuhan, China, in December 2019. In late February, the disease began to spread quickly across the world, causing serious health, social, and economic emergencies. This paper aims to forecast the short to medium-term incidence of COVID-19 epidemic through the medium of an autoregressive integrated moving average (ARIMA) model, applied to Italy, Russia, and the USA The analysis is carried out on the number of new daily confirmed COVID-19 cases, collected by Worldometer website. The best ARIMA models are Italy (4,2,4), Russia (1,2,1), and the USA (6,2,3). The results show that: i) ARIMA models are reliable enough when new daily cases begin to stabilize; ii) Italy, the USA, and Russia reached the peak of COVID-19 infections in mid-April, mid-May, and late May, respectively; and iii) Russia and the USA will require much more time than Italy to drop COVID-19 cases near zero. This may suggest the importance of the application of quick and effective lockdown measures, which have been relatively stricter in Italy. Therefore, even if the results should be interpreted with caution, ARIMA models seem to be a good tool that can help the health authorities to monitor the diffusion of the outbreak.
