Health and economic costs of early and delayed suppression and the unmitigated spread of COVID-19: The case of Australia.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2021
Historique:
received: 15 06 2020
accepted: 14 05 2021
entrez: 4 6 2021
pubmed: 5 6 2021
medline: 16 6 2021
Statut: epublish

Résumé

We compare the health and economic costs of early and delayed mandated suppression and the unmitigated spread of 'first-wave' COVID-19 infections in Australia in 2020. Using a fit-for-purpose SIQRM-compartment model for susceptible, infected, quarantined, recovered and mortalities on active cases, that we fitted from recorded data, a value of a statistical life year (VSLY) and an age-adjusted value of statistical life (A-VSL), we find that the economic costs of unmitigated suppression are multiples more than for early mandated suppression. We also find that using an equivalent VSLY welfare loss from fatalities to estimated GDP losses, drawn from survey data and our own estimates of the impact of suppression measures on the economy, means that for early suppression not to be the preferred strategy requires that Australia would have to incur more than 12,500-30,000 deaths, depending on the fatality rate with unmitigated spread, to the economy costs of early mandated suppression. We also find that early rather than delayed mandated suppression imposes much lower economy and health costs and conclude that in high-income countries, like Australia, a 'go early, go hard' strategy to suppress COVID-19 results in the lowest estimated public health and economy costs.

Identifiants

pubmed: 34086731
doi: 10.1371/journal.pone.0252400
pii: PONE-D-20-18242
pmc: PMC8177447
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0252400

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Références

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Auteurs

Tom Kompas (T)

Centre of Excellence for Biosecurity Risk Analysis, School of Biosciences and School of Ecosystem and Forest Sciences, University of Melbourne, Melbourne, Australia.

R Quentin Grafton (RQ)

Crawford School of Public Policy, Australian National University, Canberra, Australia.

Tuong Nhu Che (TN)

Australian Centre for Biosecurity and Environmental Economics, Crawford School of Public Policy, Australian National University, Canberra, Australia.

Long Chu (L)

Crawford School of Public Policy, Australian National University, Canberra, Australia.

James Camac (J)

Centre of Excellence for Biosecurity Risk Analysis, School of Biosciences, University of Melbourne, Melbourne, Australia.

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Classifications MeSH