Predicting of COVID-19 Confirmed Cases in Different Countries with ARIMA Models in 2020

  1. Tania Dehesh
  2. Heydar Ali Mardani-Fard
  3. Paria Dehesh

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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 22 th , 2020 to March 1 th , 2020. Auto Regressive Integrated Moving Average (ARIMA) model was used to predict the trend of confirmed cases. Stata version 12 and R version 3.6.2 were used. Parameters used for ARIMA were (2,1,0) for Mainland China, ARIMA(1,0,0) for South Korea, and ARIMA(3,1,0) for Thailand. 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

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  1. Version published to 10.1101/2020.03.13.20035345v2 on medRxiv
  2. ScreenIT

    SciScore for 10.1101/2020.03.13.20035345: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data source: The daily confirmed cases of COVID-2019 from January 22th, 2020 to March 1th, 2020 were collected from the official website of Johns Hopkins University (https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html), and Microsoft Excel 2019 was used to build a time-series database ARIMA models: A total number of 41 (from January 22th, 2020 to March 1th, 2020) days were collected to develop ARIMA model.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    Microsoft Excel 2016 was used to build the database of daily COVID-19 in the world and STATA version 12 software was adopted to develop the ARIMA model.
    STATA
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.03.13.20035345v1 on medRxiv