Data acquisition based COVID-19 Spread Prediction Analysis

Huynh Quoc Khanh, P. Damodharan, D.Vinoth Kumar
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Abstract

The most pressing global concern right now is Covid-19. Covid-19 affects the health, daily activities and movement of people, disrupts the global economy, damages the tourist sector, and constitutes a significant threat to global health. Finding a vaccine in a short amount of time is a success that leads to a quicker return to normalcy. Following the intricate developments of Covid-19, it is also vital to foresee the scenario early in order to aid in the construction of improved health facilities, take legislative measures, and avoid economic losses, particularly human losses. The Arima model is used in this article to forecast Covid-19 in India. Arima is well suited to forecasting data using two time-ordered data points. In this paper, data acquired by Indian states from January 1, 2020 to November 8, 2021 are used.
基于数据采集的COVID-19传播预测分析
当前全球最紧迫的问题是Covid-19。Covid-19影响人们的健康、日常活动和流动,扰乱全球经济,损害旅游业,并对全球健康构成重大威胁。在短时间内找到疫苗是一种成功,可以更快地恢复正常。在2019冠状病毒病错综复杂的事态发展之后,尽早预测未来情况也至关重要,以便帮助建设更好的卫生设施,采取立法措施,避免经济损失,特别是人员损失。本文使用Arima模型来预测印度的Covid-19。Arima非常适合使用两个时间顺序数据点来预测数据。本文使用的是印度各邦从2020年1月1日至2021年11月8日获取的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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