Predicting COVID-19 Cases and Deaths in the USA from Tests and State Populations?

David E. Allena, Michael McAleer

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
25 Downloads (Pure)


School of Mathematics and Statistics, University of Sydney, Department of Finance, Asia University, Taiwan,The paper presents a novel analysis of the US spread of the SARS-CoV-2 causes the COVID-19 disease across 50 States and 2 Territories. Simple cross-sectional regressions are able to predict quite accurately both the total number of cases and deaths, which cast doubt on measures aimed at controlling the disease via lockdowns. Population density appears to play a significant role in transmission. This throws in sharp relief the relative e_ectiveness of the at-tempts to risk manage the spread of the virus by flattening the curve' (aka planking the curve) of the speed of transmission, and the effcacy of lockdowns in terms of the spread of the disease and death rates. The algorithmic tech-niques, results and analysis presented in the paper should prove useful to the medical and health professions, science advisers, and risk management and deficision making of healthcare by state, regional and national governments in all countries.

Original languageEnglish
Pages (from-to)1-27
Number of pages27
JournalAdvances in Decision Sciences
Issue number2
Publication statusPublished - Jun 2021

Bibliographical note

JEL Classification: C22, C53, C88
Acknowledgements: The authors are most grateful for very helpful comments and suggestions from two reviewers. For financial support, the first author acknowledges the Australian Research Council, and the second author is most grateful to the Australian Research Council, Ministry of Science and Technology (MOST), Taiwan, and the Japan Society for the Promotion of Science. ∗Corresponding author Email address: (David E. Allen)

Publisher Copyright:
© 2021 Hindawi Limited. All rights reserved.


Dive into the research topics of 'Predicting COVID-19 Cases and Deaths in the USA from Tests and State Populations?'. Together they form a unique fingerprint.

Cite this