Application of the ARIMA model on the COVID-2019 epidemic dataset
Application of the ARIMA model on the COVID-2019 epidemic dataset
复制标题
DOI：
10.1016/j.dib.2020.105340
复制
发表时间：
2020-04-01
期刊：
影响因子：
1.2
通讯作者：
Ciccozzi, Massimo
中科院分区：
文献类型：
--
作者：
Benvenuto, Domenico;Giovanetti, Marta;Ciccozzi, Massimo
2019年冠状病毒病(COVID-2019)已被确认为全球威胁，目前正在使用各种数学模型进行几项研究，以预测这一流行病可能的演变。这些基于各种因素和分析的数学模型容易产生潜在的偏差。在这里，我们提出了一个简单的计量经济模型，该模型可能有助于预测2019年新冠肺炎的传播。我们对约翰霍普金斯大学的流行病学数据进行了自回归综合移动平均(ARIMA)模型预测，以预测2019年COVID-2019年的流行趋势。为了进一步比较或着眼于未来，病例定义和数据收集必须实时保持。(C)2020作者。由爱思唯尔公司出版。这是一篇基于CC by许可证(http://creativecommons.)的开放获取文章Org/许可证/by/4.0/)。
Coronavirus disease 2019 (COVID-2019) has been recognized as a global threat, and several studies are being conducted using various mathematical models to predict the probable evolution of this epidemic. These mathematical models based on various factors and analyses are subject to potential bias. Here, we propose a simple econometric model that could be useful to predict the spread of COVID-2019. We performed Auto Regressive Integrated Moving Average (ARIMA) model prediction on the Johns Hopkins epidemiological data to predict the epidemiological trend of the prevalence and incidence of COVID-2019. For further comparison or for future perspective, case definition and data collection have to be maintained in real time. (c) 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).