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About:
Forecasting of COVID-19 Confirmed Cases in Different Countries with ARIMA Models
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covidontheweb.inria.fr
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research paper
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type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
title
Forecasting of COVID-19 Confirmed Cases in Different Countries with ARIMA Models
Creator
Dehesh, Paria
Dehesh, Tania
Mardani-Fard, H
source
MedRxiv
abstract
The epidemic of a novel coronavirus illness (COVID-19) becomes as a global threat. The aim of this study is first to find the best prediction models for daily confirmed cases in countries with high number of confirmed cases in the world and second to predict confirmed cases with these models in order to have more readiness in healthcare systems. This study was conducted based on daily confirmed cases of COVID-19 that were collected from the official website of Johns Hopkins University from January 22th, 2020 to March 1th, 2020. Auto Regressive Integrated Moving Average (ARIMA) model was used to predict the trend of confirmed cases. Stata version 12 was used. Mainland China and Thailand had almost a stable trend. The trend of South Korea was decreasing and will become stable in near future. Iran and Italy had unstable trends. Mainland China and Thailand were successful in haltering COVID-19 epidemic. Investigating their protocol in this control like quarantine should be in the first line of other countries program
has issue date
2020-03-18
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bibo:doi
10.1101/2020.03.13.20035345
has license
medrxiv
sha1sum (hex)
b8f62b4c458018a4b14912d0e2bcd847f5073e47
schema:url
https://doi.org/10.1101/2020.03.13.20035345
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Forecasting of COVID-19 Confirmed Cases in Different Countries with ARIMA Models
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covid:b8f62b4c458018a4b14912d0e2bcd847f5073e47#body_text
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named entity 'confirmed'
named entity 'ARIMA'
named entity 'Countries'
named entity 'Countries'
named entity 'CASES'
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