论文标题
比较Arima，ET，NNAR和混合模型，以预测意大利的第二波Covid-19
Comparison of ARIMA, ETS, NNAR and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy
论文作者
论文摘要
冠状病毒病（Covid-19）是一项严重的持续的新型大流行病，于2019年12月在中国武汉出现。截至10月13日，爆发已经迅速蔓延到世界各地，影响了超过3,800万人，并造成超过100万人死亡。 In this article, I analysed several time series forecasting methods to predict the spread of COVID-19 second wave in Italy, over the period after October 13, 2020. I used an autoregressive model (ARIMA), an exponential smoothing state space model (ETS), a neural network autoregression model (NNAR), and the following hybrid combinations of them: ARIMA-ETS, ARIMA-NNAR, ETS-NNAR, and Arima-et-nnar。关于数据，我预测了患有轻度症状的患者数量以及重症监护病房（ICU）。数据是指2020年2月21日至2020年10月13日的期间，并从意大利卫生部（www.salute.gov.it）的网站上提取。结果表明，除Arima-ETS外，i）杂交模型通过优于各自的单个模型来捕获线性和非线性流行模式； ii）与症状轻度症状相关的相关住院数量，在接下来的几周内，ICU的数量将在大约50-60天内达到峰值，即至少在2020年12月中旬达到高峰。为了解决即将到来的Covid-19第二波，一方面，有必要雇用医护人员并实施足够的医院设施，保护设备以及普通的重症监护床；另一方面，例如，通过改善公共交通和采用双班教育系统来增强社会疏远可能是有用的。
Coronavirus disease (COVID-19) is a severe ongoing novel pandemic that has emerged in Wuhan, China, in December 2019. As of October 13, the outbreak has spread rapidly across the world, affecting over 38 million people, and causing over 1 million deaths. In this article, I analysed several time series forecasting methods to predict the spread of COVID-19 second wave in Italy, over the period after October 13, 2020. I used an autoregressive model (ARIMA), an exponential smoothing state space model (ETS), a neural network autoregression model (NNAR), and the following hybrid combinations of them: ARIMA-ETS, ARIMA-NNAR, ETS-NNAR, and ARIMA-ETS-NNAR. About the data, I forecasted the number of patients hospitalized with mild symptoms, and in intensive care units (ICU). The data refer to the period February 21, 2020-October 13, 2020 and are extracted from the website of the Italian Ministry of Health (www.salute.gov.it). The results show that i) the hybrid models, except for ARIMA-ETS, are better at capturing the linear and non-linear epidemic patterns, by outperforming the respective single models; and ii) the number of COVID-19-related hospitalized with mild symptoms and in ICU will rapidly increase in the next weeks, by reaching the peak in about 50-60 days, i.e. in mid-December 2020, at least. To tackle the upcoming COVID-19 second wave, on one hand, it is necessary to hire healthcare workers and implement sufficient hospital facilities, protective equipment, and ordinary and intensive care beds; and on the other hand, it may be useful to enhance social distancing by improving public transport and adopting the double-shifts schooling system, for example.
