Evidence map›Paper›PMID 34136653›Full record

ArticleHealth science reports2021

A benefit-cost analysis of different response scenarios to COVID-19: A case study.

David C Cook, Rob W Fraser, Simon J McKirdy

Abstract read
In one paragraph

Article in Health science reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

David C CookSchool of Agriculture and Environment The University of Western Australia Perth Western Australia Australia.ORCID https://orcid.org/0000-0002-2954-7697
Rob W FraserSchool of Agriculture and Environment The University of Western Australia Perth Western Australia Australia.
Simon J McKirdyHarry Butler Research Institute Murdoch University Perth Western Australia Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis paper compares the direct benefits to the State of Western Australia from employing a "suppression" policy response to the COVID-19 pandemic rather than a "herd immunity" approach.

methodsAn S-I-R (susceptible-infectious-resolved) model is used to estimate the likely benefits of a suppression COVID-19 response compared to a herd immunity alternative. Direct impacts of the virus are calculated on the basis of sick leave, hospitalizations, and fatalities, while indirect impacts related to response actions are excluded.

resultsPreliminary modeling indicates that approximately 1700 vulnerable person deaths are likely to have been prevented over 1 year from adopting a suppression response rather than a herd immunity response, and approximately 4500 hospitalizations. These benefits are valued at around AUD4.7 billion. If a do nothing policy had been adopted, the number of people in need of hospitalization is likely to have overwhelmed the hospital system within 50 days of the virus being introduced. Maximum hospital capacity is unlikely to be reached in either a suppression policy or a herd immunity policy.

conclusionUsing early international estimates to represent the negative impact each type of policy response is likely to have on gross state product, results suggest the benefit-cost ratio for the suppression policy is slightly higher than that of the herd immunity policy, but both benefit-cost ratios are less than one.

Indexed as

natural disasterpolicy makingpublic policysimulation modeling

Identifiers

PMID34136653
PMCPMC8177900

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.