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Coronavirus Infections and Deaths by Poverty Status: The Effects of Social Distancing

Author

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  • Juergen Jung

    (Department of Economics, Towson University)

  • James Manley

    (Department of Economics, Towson University)

  • Vinish Shrestha

    (Department of Economics, Towson University)

Abstract

We study the spread of COVID-19 infections and deaths by county poverty level in the US. In the beginning of the pandemic, counties with either very low poverty levels or very high poverty levels reported the highest numbers of cases. A U-shaped relationship prevails for counties with high population density while among counties with low population density, only poorer counties report high incidence rates of COVID-19. Second, we discuss the pattern of infections spreading from higher to lower income counties. Third, we show that stay-at-home mandates caused significantly higher reductions in mobility in high income counties that experienced adverse weather shocks than counties that did not. These effects are not present in counties with high poverty rates. Using weather shocks in combination with stay-at-home mandates as an instrument for social distancing, we find that measures taken to promote social distancing helped curb infections in high income counties but not in low income counties. These results have important policy implications for containing the spread of infectious diseases in the future.

Suggested Citation

  • Juergen Jung & James Manley & Vinish Shrestha, 2020. "Coronavirus Infections and Deaths by Poverty Status: The Effects of Social Distancing," Working Papers 2020-03, Towson University, Department of Economics, revised Dec 2020.
    • Handle: RePEc:tow:wpaper:2020-03
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    2. James Davies, 2021. "Economic Inequality and Covid-19 Death Rates in the First Wave, a Cross-Country Analysis," CESifo Working Paper Series 8957, CESifo.
    3. Aldo Carranza & Marcel Goic & Eduardo Lara & Marcelo Olivares & Gabriel Y. Weintraub & Julio Covarrubia & Cristian Escobedo & Natalia Jara & Leonardo J. Basso, 2022. "The Social Divide of Social Distancing: Shelter-in-Place Behavior in Santiago During the Covid-19 Pandemic," Management Science, INFORMS, vol. 68(3), pages 2016-2027, March.
    4. 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).
    5. Mellacher, Patrick, 2023. "The impact of corona populism: Empirical evidence from Austria and theory," Journal of Economic Behavior & Organization, Elsevier, vol. 209(C), pages 113-140.
    6. Melo, Vitor, 2022. "Intended and Unintended Effects of Nursing Home Isolation Measures," Working Papers 12244, George Mason University, Mercatus Center.
    7. Lili Li & Araz Taeihagh & Si Ying Tan, 2023. "A scoping review of the impacts of COVID-19 physical distancing measures on vulnerable population groups," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    8. David A. Sánchez-Páez, 2022. "Effects of income inequality on COVID-19 infections and deaths during the first wave of the pandemic: Evidence from European countries," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 20(1), pages 85-106.
    9. David E. Bloom & Michael Kuhn & Klaus Prettner, 2022. "Modern Infectious Diseases: Macroeconomic Impacts and Policy Responses," Journal of Economic Literature, American Economic Association, vol. 60(1), pages 85-131, March.
    10. Patrick Carlin & Brian E. Dixon & Kosali I. Simon & Ryan Sullivan & Coady Wing, 2022. "How Undervalued is the Covid-19 Vaccine? Evidence from Discrete Choice Experiments and VSL Benchmarks," NBER Working Papers 30118, National Bureau of Economic Research, Inc.
    11. INOUE Tomoo & OKIMOTO Tatsuyoshi, 2022. "Exploring the Dynamic Relationship between Mobility and the Spread of COVID-19, and the Role of Vaccines," Discussion papers 22011, Research Institute of Economy, Trade and Industry (RIETI).
    12. Deiana, Claudio & Geraci, Andrea & Mazzarella, Gianluca & Sabatini, Fabio, 2022. "Can relief measures nudge compliance in a public health crisis? Evidence from a kinked fiscal policy rule," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 407-428.
    13. Albani, Viviana & Welsh, Claire E. & Brown, Heather & Matthews, Fiona E. & Bambra, Clare, 2022. "Explaining the deprivation gap in COVID-19 mortality rates: A decomposition analysis of geographical inequalities in England," Social Science & Medicine, Elsevier, vol. 311(C).
    14. Cho, Jung-Hoon & Kim, Dong-Kyu & Kim, Eui-Jin, 2022. "Multi-scale causality analysis between COVID-19 cases and mobility level using ensemble empirical mode decomposition and causal decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    15. 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.
    16. Shimaa Elkomy & Tim Jackson, 2024. "Health resilience and the global pandemic: The effect of social conditions on the COVID‐19 mortality rate," Journal of International Development, John Wiley & Sons, Ltd., vol. 36(5), pages 2342-2371, July.

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    More about this item

    Keywords

    Coronavirus; pandemic; SARS-CoV-2; COVID-19; heterogeneous health effects; infections by poverty status; death rates by poverty status.;
    All these keywords.

    JEL classification:

    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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