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Measuring Geographical Disparities in England at the Time of COVID-19: Results Using a Composite Indicator of Population Vulnerability

Author

Listed:
  • Nicodemo, Catia

    (University of Oxford)

  • Barzin, Samira

    (Oxford University Press)

  • Lasserson, Daniel S.

    (University of Birmingham)

  • Moscone, Francesco

    (Brunel University)

  • Redding, Stuart

    (University of Oxford)

  • Shaikh, Mujaheed

    (Hertie School of Governance)

  • Cavalli, Nicolò

    (Nuffield College, Oxford)

Abstract

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 – 191 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.

Suggested Citation

  • Nicodemo, Catia & Barzin, Samira & Lasserson, Daniel S. & Moscone, Francesco & Redding, Stuart & Shaikh, Mujaheed & Cavalli, Nicolò, 2020. "Measuring Geographical Disparities in England at the Time of COVID-19: Results Using a Composite Indicator of Population Vulnerability," IZA Discussion Papers 13757, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp13757
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    References listed on IDEAS

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    5. Paul Rutter & Oliver Mytton & Matthew Mak & Liam Donaldson, 2012. "Socio-economic disparities in mortality due to pandemic influenza in England," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 57(4), pages 745-750, August.
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    Cited by:

    1. Jamie M. Madden & Simon More & Conor Teljeur & Justin Gleeson & Cathal Walsh & Guy McGrath, 2021. "Population Mobility Trends, Deprivation Index and the Spatio-Temporal Spread of Coronavirus Disease 2019 in Ireland," IJERPH, MDPI, vol. 18(12), pages 1-16, June.
    2. Anna Zaytseva & Pierre Verger & Bruno Ventelou, 2021. "United, we can be stronger! French integrated general practitioners had better chronic care follow-up during lockdown," Working Papers halshs-03227216, HAL.
    3. Madia, Joan E. & Moscone, Francesco & Nicodemo, Catia, 2023. "Informal care, older people, and COVID-19: Evidence from the UK," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 468-488.

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    More about this item

    Keywords

    health inequalities; geographical disparity; pandemic; emergency preparedness; index of vulnerability; COVID-19;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • J28 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Safety; Job Satisfaction; Related Public Policy
    • I1 - Health, Education, and Welfare - - Health

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