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
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
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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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