Evidence map›Paper›PMID 36698139›Full record

ArticleHealth research policy and systems2023

Standardising policy and technology responses in the immediate aftermath of a pandemic: a comparative and conceptual framework.

Naomi Moy, Marcello Antonini, Mattias Kyhlstedt, Gianluca Fiorentini, Francesco Paolucci

Open access · goldAbstract read
In one paragraph

Article in Health research policy and systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 10% of its field
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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
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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

5 authors at 3 institutions in 2 countries.

Naomi MoyDepartment of Sociology and Business Law, University of Bologna, Strada Maggiore 45, 40126, Bologna, Italy.ORCID http://orcid.org/0000-0003-0413-9053
Marcello AntoniniSchool of Medicine and Public Health, University of Newcastle, University Dr , Callaghan, NSW, 2308, Australia. marcello.antonini@uon.edu.au.ORCID http://orcid.org/0000-0001-5816-2289
Mattias KyhlstedtSynergus RWE, Stationsvägen 18, 184 50 , Åkersberga, Sweden.ORCID http://orcid.org/0000-0002-7055-8849
Gianluca FiorentiniDepartment of Economics, University of Bologna, Piazza Scaravilli 2, 40126, Bologna, Italy.ORCID http://orcid.org/0000-0003-4197-9924
Francesco PaolucciDepartment of Sociology and Business Law, University of Bologna, Strada Maggiore 45, 40126, Bologna, Italy.ORCID http://orcid.org/0000-0001-6173-5324
University of Newcastle Australia · AUQueensland University of Technology · AUUniversity of Bologna · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe initial policy response to the COVID-19 pandemic has differed widely across countries. Such variability in government interventions has made it difficult for policymakers and health research systems to compare what has happened and the effectiveness of interventions across nations. Timely information and analysis are crucial to addressing the lag between the pandemic and government responses to implement targeted interventions to alleviate the impact of the pandemic.

methodsTo examine the effect government interventions and technological responses have on epidemiological and economic outcomes, this policy paper proposes a conceptual framework that provides a qualitative taxonomy of government policy directives implemented in the immediate aftermath of a pandemic announcement and before vaccines are implementable. This framework assigns a gradient indicating the intensity and extent of the policy measures and applies the gradient to four countries that share similar institutional features but different COVID-19 experiences: Italy, New Zealand, the United Kingdom and the United States of America.

resultsUsing the categorisation framework allows qualitative information to be presented, and more specifically the gradient can show the dynamic impact of policy interventions on specific outcomes. We have observed that the policy categorisation described here can be used by decision-makers to examine the impacts of major viral outbreaks such as SARS-CoV-2 on health and economic outcomes over time. The framework allows for a visualisation of the frequency and comparison of dominant policies and provides a conceptual tool to assess how dominant interventions (and innovations) affect different sets of health and non-health related outcomes during the response phase to the pandemic.

conclusionsPolicymakers and health researchers should converge toward an optimal set of policy interventions to minimize the costs of the pandemic (i.e., health and economic), and facilitate coordination across governance levels before effective vaccines are produced. The proposed framework provides a useful tool to direct health research system resources and build a policy benchmark for future viral outbreaks where vaccines are not readily available.

Indexed as

COVID-19Disease OutbreaksHumansPandemicsPolicySARS-CoV-2COVID-19Economic outcomesHealth outcomesHealth research systemsPolicy categorisationPolicy gradientPolicy interventionsPublic health crisis

Identifiers

PMID36698139
PMCPMC9875766
OpenAlexW4317937555

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.