Evidence map›Paper›PMID 32994257›Full record

ArticleBMJ open2020

Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability.

Catia Nicodemo, Samira Barzin, Nicolo' Cavalli, Daniel Lasserson, Francesco Moscone, Stuart Redding, Mujaheed Shaikh

Abstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Article
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  3. 'BMJ global health · 2023
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  7. Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023
    Article
  8. Informal care, older people, and COVID-19: Evidence from the UK.Journal of economic behavior & organization · 2023
    Article
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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

7 authors.

Catia NicodemoNuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK catia.nicodemo@economics.ox.ac.uk.ORCID 0000-0002-2800-0083
Samira BarzinMathematical Institute, Oxford University, Oxford, UK.
Nicolo' CavalliNuffield College, University of Oxford, Oxford, UK.
Daniel LassersonInstitute of Applied Health Research, University of Birmingham, Birmingham, UK.ORCID 0000-0001-8274-5580
Francesco MosconeBrunel University of London, London, UK.
Stuart ReddingNuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.
Mujaheed ShaikhHertie School, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe growth of COVID-19 infections in England raises questions about system vulnerability. Several factors that vary across geographies, such as age, existing disease prevalence, medical resource availability and deprivation, can trigger adverse effects on the National Health System during a pandemic. In this paper, we present data on these factors and combine them to create an index to show which areas are more exposed. This technique can help policy makers to moderate the impact of similar pandemics.

designWe combine several sources of data, which describe specific risk factors linked with the outbreak of a respiratory pathogen, that could leave local areas vulnerable to the harmful consequences of large-scale outbreaks of contagious diseases. We combine these measures to generate an index of community-level vulnerability.

setting91 Clinical Commissioning Groups (CCGs) in England.

main outcome measuresWe merge 15 measures spatially to generate an index of community-level vulnerability. These measures cover prevalence rates of high-risk diseases; proxies for the at-risk population density; availability of staff and quality of healthcare facilities.

resultsWe find that 80% of CCGs that score in the highest quartile of vulnerability are located in the North of England (24 out of 30). Here, vulnerability stems from a faster rate of population ageing and from the widespread presence of underlying at-risk diseases. These same areas, especially the North-East Coast areas of Lancashire, also appear vulnerable to adverse shocks to healthcare supply due to tighter labour markets for healthcare personnel. Importantly, our index correlates with a measure of social deprivation, indicating that these communities suffer from long-standing lack of economic opportunities and are characterised by low public and private resource endowments.

conclusionsEvidence-based policy is crucial to mitigate the health impact of pandemics such as COVID-19. While current attention focuses on curbing rates of contagion, we introduce a vulnerability index combining data that can help policy makers identify the most vulnerable communities. We find that this index is positively correlated with COVID-19 deaths and it can thus be used to guide targeted capacity building. These results suggest that a stronger focus on deprived and vulnerable communities is needed to tackle future threats from emerging and re-emerging infectious disease.

Indexed as

Communicable Disease ControlCoronavirus InfectionsPandemicsPneumonia, ViralBetacoronavirusCOVID-19Disease Transmission, InfectiousEnglandHealth ResourcesHealth Services AccessibilityHealth Status DisparitiesHumansNeeds AssessmentPrevalencePublic HealthQuality Improvementadult intensive & critical carehealth economicshealth policy

Identifiers

PMID32994257
PMCPMC7526277

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LicenceCC BY
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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.