Forecasting the Trend of Covid-19 Epidemic

A. Bansal, Aarushi Bhardwaj, Aman Sharma
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引用次数: 1

Abstract

Corona virus also known as COVID 19 is a critical ongoing pandemic that is on a rise across the globe. Italy and China have been considered as one of the main epicentres from where the pandemic came into full effect. Here, the highest death rates across the world are registered as a consequence of COVID-19. One of the leading countries, the USA has also been in the registered countries with an increasing number of cases of COVID 19. In this paper ARIMA model that is an auto regressive integrated moving average model is used to help forecast the epidemic trend over a period of time (i.e. April 2020). The dataset used is from the Italian epidemiological data at National and Regional level. It refers to the number of daily confirmed cases as well as the fatalities registered by Italian Ministry of Health. The model has various advantages like it is easy to use, to manage and a suitable model for forecasting purposes. Moreover, it gives a thorough clarity of basic trends, by predicting the hypothetical epidemic's inflection point and final size.
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新冠肺炎疫情趋势预测
冠状病毒也被称为COVID - 19,是一种严重的持续大流行,在全球范围内呈上升趋势。意大利和中国被认为是疫情全面爆发的主要震中之一。在这里,COVID-19导致的全球死亡率最高。美国是主要国家之一,也是新冠肺炎确诊病例不断增加的国家之一。本文使用自回归综合移动平均模型ARIMA模型来帮助预测一段时间(即2020年4月)的疫情趋势。所使用的数据集来自意大利国家和地区一级的流行病学数据。它指的是意大利卫生部登记的每日确诊病例数和死亡人数。该模型具有易于使用、易于管理和适合预测等优点。此外,它通过预测假想流行病的拐点和最终规模,彻底明确了基本趋势。
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