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

OBJECTIVES: The 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 durin...

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Autores principales: Nicodemo, Catia, Barzin, Samira, Cavalli, Nicolo', Lasserson, Daniel, Moscone, Francesco, Redding, Stuart, Shaikh, Mujaheed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7526277/
https://www.ncbi.nlm.nih.gov/pubmed/32994257
http://dx.doi.org/10.1136/bmjopen-2020-039749
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author Nicodemo, Catia
Barzin, Samira
Cavalli, Nicolo'
Lasserson, Daniel
Moscone, Francesco
Redding, Stuart
Shaikh, Mujaheed
author_facet Nicodemo, Catia
Barzin, Samira
Cavalli, Nicolo'
Lasserson, Daniel
Moscone, Francesco
Redding, Stuart
Shaikh, Mujaheed
author_sort Nicodemo, Catia
collection PubMed
description OBJECTIVES: The 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. DESIGN: We 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. SETTING: 91 Clinical Commissioning Groups (CCGs) in England. MAIN OUTCOME MEASURES: We 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. RESULTS: We 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. CONCLUSIONS: Evidence-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.
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spelling pubmed-75262772020-10-19 Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability Nicodemo, Catia Barzin, Samira Cavalli, Nicolo' Lasserson, Daniel Moscone, Francesco Redding, Stuart Shaikh, Mujaheed BMJ Open Health Policy OBJECTIVES: The 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. DESIGN: We 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. SETTING: 91 Clinical Commissioning Groups (CCGs) in England. MAIN OUTCOME MEASURES: We 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. RESULTS: We 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. CONCLUSIONS: Evidence-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. BMJ Publishing Group 2020-09-29 /pmc/articles/PMC7526277/ /pubmed/32994257 http://dx.doi.org/10.1136/bmjopen-2020-039749 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Health Policy
Nicodemo, Catia
Barzin, Samira
Cavalli, Nicolo'
Lasserson, Daniel
Moscone, Francesco
Redding, Stuart
Shaikh, Mujaheed
Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability
title Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability
title_full Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability
title_fullStr Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability
title_full_unstemmed Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability
title_short Measuring geographical disparities in England at the time of COVID-19: results using a composite indicator of population vulnerability
title_sort measuring geographical disparities in england at the time of covid-19: results using a composite indicator of population vulnerability
topic Health Policy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7526277/
https://www.ncbi.nlm.nih.gov/pubmed/32994257
http://dx.doi.org/10.1136/bmjopen-2020-039749
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