 Predicting COVID-19 Cases and Deaths in the USA from Tests and State PopulationsDavid Allen and Michael McAleer Advances in Decision Sciences, 2021, vol. 25, issue 2, 1-27 Abstract: 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 effectiveness 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 efficacy 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 de- cision making of healthcare by state, regional and national governments in all countries. Keywords: Risk management; Curve projection; Live data; Global pandemic; COVID 19; Lockdown; CFR. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:aag:wpaper:v:25:y:2021:i:2:p:1-27 Access Statistics for this article More articles in Advances in Decision Sciences from Asia University, Taiwan Contact information at EDIRC. |
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