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

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Abstract

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
Volume25
Issue number2
DOIs
Publication statusPublished - Jun 2021

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