A Bayes Decision Rule to Assist Policymakers during a Pandemic.
Healthcare (Basel)
; 9(8)2021 Aug 09.
Article
in English
| MEDLINE | ID: covidwho-1376792
ABSTRACT
A new decision rule based on net benefit per capita is proposed and exemplified with the aim of assisting policymakers in deciding whether to lockdown or reopen an economy-fully or partially-amidst a pandemic. Bayesian econometric models using Markov chain Monte Carlo algorithms are used to quantify this rule, which is illustrated via several sensitivity analyses. While we use COVID-19 data from the United States to demonstrate the ideas, our approach is invariant to the choice of pandemic and/or country. The actions suggested by our decision rule are consistent with the closing and reopening of the economies made by policymakers in Florida, Texas, and New York; these states were selected to exemplify the methodology since they capture the broad spectrum of COVID-19 outcomes in the U.S.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Language:
English
Year:
2021
Document Type:
Article
Affiliation country:
Healthcare9081023
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