Evidence map›Paper›PMID 37344781›Full record

ArticleBMC public health2023

Areas of enduring COVID-19 prevalence: drivers of prevalence and mitigating strategies.

Catherine Lewis, Sheena Johnson, Angelique Hartwig, Janet Ubido, Anna Coleman, Nicola Gartland, Atiya Kamal, Amit Gaokar, Christopher J Armitage, David Fishwick and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

11 authors at 4 institutions in 1 country.

Catherine LewisDivision of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, England. catherine.lewis@manchester.ac.uk.
Sheena JohnsonAlliance Manchester Business School, University of Manchester, Manchester, England.
Angelique HartwigAlliance Manchester Business School, University of Manchester, Manchester, England.
Janet UbidoDivision of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, England.
Anna ColemanDivision of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, England.
Nicola GartlandDivision of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, England.
Atiya KamalBirmingham City University, Birmingham, England.
Amit GaokarRochdale Borough Council, Manchester, England.
Christopher J ArmitageManchester Centre for Health Psychology, University of Manchester, Manchester, England.
David FishwickHealth and Safety Executive (HSE), Liverpool, England.
Martie van TongerenDivision of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, England.
University of Manchester · GBBirmingham City University · GBHealth and Safety Executive · GBRochdale Infirmary · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUK local authorities that experienced sustained high levels of COVID-19 between 1st March 2020 and 28th February 2021 were described by the UK Scientific Advisory Group for Emergencies as areas of enduring prevalence. This research was carried out in order to examine the views of local authority Directors of Public Health, who played a crucial role in the local response to COVID-19, on reasons for sustained high levels of prevalence in some areas, alongside an investigation of the mitigation strategies that they implemented during the course of the pandemic.

methodsInterviews were conducted with Directors of Public Health in 19 local authority areas across England, between July and November 2021. This included nine areas identified as areas of enduring prevalence and ten 'comparison' areas.

resultsThe outcomes of this study suggests that the geographical differences in prevalence rates are strongly influenced by health inequalities. Structural factors including deprivation, employment, and housing, due to their disproportionate impact on specific groups, converged with demographic factors, including ethnicity and age, and vaccination rates, and were identified as the main drivers of enduring prevalence. There are key differences in these drivers both within and, to a lesser extent, between local authorities. Other than these structural barriers, no major differences in facilitators or barriers to COVID-19 mitigation were identified between areas of varying prevalence. The main features of successful mitigation strategies were a locally tailored approach and partnership working involving local authority departments working with local health, community, voluntary and business organisations.

conclusionsThis study is the first to add the voices of Directors of Public Health, who played a crucial role in the local COVID-19 response. Areas of enduring prevalence existed during the pandemic which were caused by a complex mix of structural factors related to inequalities. Participants advised that more research is needed on the effectiveness of mitigation strategies and other measures to reduce the impact of structural inequalities, to better understand the factors that drive prevalence. This would include an assessment of how these factors combine to predict transmission and how this varies between different areas.

Indexed as

COVID-19EmploymentEnglandHumansPrevalencePublic HealthCommunity engagementCOVID-19DeprivationEmploymentHealth inequalitiesPartnership working

Identifiers

PMID37344781
PMCPMC10286421
OpenAlexW4381549855

What OpenQuestion holds

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LicenceCC BY
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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.