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    Global short-term forecasting of COVID-19 cases


    de Paula Oliveira, Thiago and de Andrade Moral, Rafael (2021) Global short-term forecasting of COVID-19 cases. Scientific Reports, 11 (7555). pp. 1-9. ISSN 2045-2322

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    Abstract

    The continuously growing number of COVID-19 cases pressures healthcare services worldwide. Accurate short-term forecasting is thus vital to support country-level policy making. The strategies adopted by countries to combat the pandemic vary, generating diferent uncertainty levels about the actual number of cases. Accounting for the hierarchical structure of the data and accommodating extra-variability is therefore fundamental. We introduce a new modelling framework to describe the pandemic’s course with great accuracy and provide short-term daily forecasts for every country in the world. We show that our model generates highly accurate forecasts up to seven days ahead and use estimated model components to cluster countries based on recent events. We introduce statistical novelty in terms of modelling the autoregressive parameter as a function of time, increasing predictive power and fexibility to adapt to each country. Our model can also be used to forecast the number of deaths, study the efects of covariates (such as lockdown policies), and generate forecasts for smaller regions within countries. Consequently, it has substantial implications for global planning and decision making. We present forecasts and make all results freely available to any country in the world through an online Shiny dashboard.

    Item Type: Article
    Additional Information: Open Access: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Cite as: Oliveira, T.P., Moral, R.A. Global short-term forecasting of COVID-19 cases. Sci Rep 11, 7555 (2021). https://doi.org/10.1038/s41598-021-87230-x. Supplementary Information: The online version contains supplementary material available at https://doi.org/ 10.1038/s41598-021-87230-x.
    Keywords: global; short-term; forecasting; covid 19 cases;
    Academic Unit: Faculty of Science and Engineering > Mathematics and Statistics
    Item ID: 14610
    Identification Number: https://doi.org/10.1038/s41598-021-87230-x
    Depositing User: Rafael de Andrade Moral
    Date Deposited: 19 Jul 2021 15:20
    Journal or Publication Title: Scientific Reports
    Publisher: Nature Publishing Group
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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