{"title":"Data acquisition based COVID-19 Spread Prediction Analysis","authors":"Huynh Quoc Khanh, P. Damodharan, D.Vinoth Kumar","doi":"10.1109/ICEARS53579.2022.9752039","DOIUrl":null,"url":null,"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.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEARS53579.2022.9752039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.