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Socioeconomic Determinants of COVID-19 Infections and Mortality: Evidence from England and Wales

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  • Sa, Filipa

    (King's College London)

Abstract

I use simple correlations and regression analysis to study how the number of confirmed Covid-19 cases and the number of deaths with Covid-19 per 100,000 people is related with the socioeconomic characteristics of local areas in England and Wales. I find that local areas that have larger households, worse levels of self-reported health and a larger fraction of people using public transport have more Covid-19 infections per 100,000 people. For mortality, household size and use of public transport are less important, but there is a clear relation with age, ethnicity and self-reported health. Local areas with an older population, a larger share of black or Asian population and worse levels of self-reported health have more Covid-19 deaths per 100,000 people. To prevent the spread of infection and reduce mortality, policymakers should introduce measures to improve housing conditions and improve the health of the population. Also, as many countries now begin to relax lockdown measures, they should pay particular attention to reducing the risk of infection in public transport.

Suggested Citation

  • Sa, Filipa, 2020. "Socioeconomic Determinants of COVID-19 Infections and Mortality: Evidence from England and Wales," IZA Policy Papers 159, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izapps:pp159
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    References listed on IDEAS

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    1. George J. Borjas, 2020. "Demographic Determinants of Testing Incidence and COVID-19 Infections in New York City Neighborhoods," NBER Working Papers 26952, National Bureau of Economic Research, Inc.
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    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Economic consequences > Socioeconomic status

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    Cited by:

    1. Brandily, Paul & Brébion, Clément & Briole, Simon & Khoury, Laura, 2021. "A poorly understood disease? The impact of COVID-19 on the income gradient in mortality over the course of the pandemic," European Economic Review, Elsevier, vol. 140(C).
    2. Roy Cerqueti & Raffaella Coppier & Alessandro Girardi & Marco Ventura, 2022. "The sooner the better: lives saved by the lockdown during the COVID-19 outbreak. The case of Italy [Using synthetic controls: Feasibility, data requirements, and methodological aspects]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 46-70.
    3. Laliotis, Ioannis & Minos, Dimitrios, 2022. "Religion, social interactions, and COVID-19 incidence in Western Germany," European Economic Review, Elsevier, vol. 141(C).
    4. Brandily, Paul & Brébion, Clément & Briole, Simon & Khoury, Laura, 2020. "A Poorly Understood Disease? The Unequal Distribution of Excess Mortality Due to COVID-19 Across French Municipalities," Discussion Paper Series in Economics 15/2020, Norwegian School of Economics, Department of Economics.
    5. Daniel L. Millimet & Christopher F. Parmeter, 2022. "COVID‐19 severity: A new approach to quantifying global cases and deaths," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1178-1215, July.
    6. Paul Brandily & Clément Brébion & Simon Briole & Laura Khoury, 2021. "A Poorly Understood Disease? The Evolution of the Income Gradient in Excess Mortality Due to COVID-19 within Urban Areas," Working Papers halshs-03154551, HAL.
    7. Armillei, Francesco & Filippucci, Francesco & Fletcher, Thomas, 2021. "Did Covid-19 hit harder in peripheral areas? The case of Italian municipalities," Economics & Human Biology, Elsevier, vol. 42(C).

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    More about this item

    Keywords

    COVID-19;

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health

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