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Association of poor housing conditions with COVID-19 incidence and mortality across US counties

Author

Listed:
  • Khansa Ahmad
  • Sebhat Erqou
  • Nishant Shah
  • Umair Nazir
  • Alan R Morrison
  • Gaurav Choudhary
  • Wen-Chih Wu

Abstract

Objective: Poor housing conditions have been linked with worse health outcomes and infectious disease spread. Since the relationship of poor housing conditions with incidence and mortality of COVID-19 is unknown, we investigated the association between poor housing condition and COVID-19 incidence and mortality in US counties. Methods: We conducted cross-sectional analysis of county-level data from the US Centers for Disease Control, US Census Bureau and John Hopkins Coronavirus Resource Center for 3135 US counties. The exposure of interest was percentage of households with poor housing conditions (one or greater of: overcrowding, high housing cost, incomplete kitchen facilities, or incomplete plumbing facilities). Outcomes were incidence rate ratios (IRR) and mortality rate ratios (MRR) of COVID-19 across US counties through 4/21/2020. Multilevel generalized linear modeling (with total population of each county as a denominator) was utilized to estimate relative risk of incidence and mortality related to poor housing conditions with adjustment for population density and county characteristics including demographics, income, education, prevalence of medical comorbidities, access to healthcare insurance and emergency rooms, and state-level COVID-19 test density. We report incidence rate ratios (IRRs) and mortality ratios (MRRs) for a 5% increase in prevalence in households with poor housing conditions. Results: Across 3135 US counties, the mean percentage of households with poor housing conditions was 14.2% (range 2.7% to 60.2%). On April 21st, the mean (SD) number of cases and deaths of COVID-19 were 255.68 (2877.03) cases and 13.90 (272.22) deaths per county, respectively. In the adjusted models standardized by county population, with each 5% increase in percent households with poor housing conditions, there was a 50% higher risk of COVID-19 incidence (IRR 1.50, 95% CI: 1.38–1.62) and a 42% higher risk of COVID-19 mortality (MRR 1.42, 95% CI: 1.25–1.61). Results remained similar using earlier timepoints (3/31/2020 and 4/10/2020). Conclusions and relevance: Counties with a higher percentage of households with poor housing had higher incidence of, and mortality associated with, COVID-19. These findings suggest targeted health policies to support individuals living in poor housing conditions should be considered in further efforts to mitigate adverse outcomes associated with COVID-19.

Suggested Citation

  • Khansa Ahmad & Sebhat Erqou & Nishant Shah & Umair Nazir & Alan R Morrison & Gaurav Choudhary & Wen-Chih Wu, 2020. "Association of poor housing conditions with COVID-19 incidence and mortality across US counties," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-13, November.
    • Handle: RePEc:plo:pone00:0241327
    DOI: 10.1371/journal.pone.0241327
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    References listed on IDEAS

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    1. Dunn, James R. & Hayes, Michael V., 2000. "Social inequality, population health, and housing: a study of two Vancouver neighborhoods," Social Science & Medicine, Elsevier, vol. 51(4), pages 563-587, August.
    2. Krieger, J. & Higgins, D.L., 2002. "Housing and health: Time again for public health action," American Journal of Public Health, American Public Health Association, vol. 92(5), pages 758-768.
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    2. Arnab K Ghosh & Sara Venkatraman & Evgeniya Reshetnyak & Mangala Rajan & Anjile An & John K Chae & Mark A Unruh & David Abramson & Charles DiMaggio & Nathaniel Hupert, 2022. "Association between city-wide lockdown and COVID-19 hospitalization rates in multigenerational households in New York City," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-13, March.
    3. Emanuele Giorgi & Lucía Martín López & Ruben Garnica-Monroy & Aleksandra Krstikj & Carlos Cobreros & Miguel A. Montoya, 2021. "Co-Housing Response to Social Isolation of COVID-19 Outbreak, with a Focus on Gender Implications," Sustainability, MDPI, vol. 13(13), pages 1-25, June.
    4. ArunKumar, K.E. & Kalaga, Dinesh V. & Kumar, Ch. Mohan Sai & Kawaji, Masahiro & Brenza, Timothy M, 2021. "Forecasting of COVID-19 using deep layer Recurrent Neural Networks (RNNs) with Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) cells," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    5. Lateef, Rusan & Alaggia, Ramona & Collin-Vézina, Delphine, 2021. "A scoping review on psychosocial consequences of pandemics on parents and children: Planning for today and the future," Children and Youth Services Review, Elsevier, vol. 125(C).
    6. Isabel Aguilar-Palacio & Lina Maldonado & Sara Malo & Raquel Sánchez-Recio & Iván Marcos-Campos & Rosa Magallón-Botaya & Mª José Rabanaque, 2021. "COVID-19 Inequalities: Individual and Area Socioeconomic Factors (Aragón, Spain)," IJERPH, MDPI, vol. 18(12), pages 1-15, June.
    7. Katharine Robb & Ashley Marcoux & Jorrit de Jong, 2021. "Further Inspection: Integrating Housing Code Enforcement and Social Services to Improve Community Health," IJERPH, MDPI, vol. 18(22), pages 1-13, November.
    8. Jianwei Huang & Mei-Po Kwan, 2022. "Examining the Influence of Housing Conditions and Daily Greenspace Exposure on People’s Perceived COVID-19 Risk and Distress," IJERPH, MDPI, vol. 19(14), pages 1-19, July.
    9. Valenzuela-Levi, N. & Echiburu, T. & Correa, J. & Hurtubia, R. & Muñoz, J.C., 2021. "Housing and accessibility after the COVID-19 pandemic: Rebuilding for resilience, equity and sustainable mobility," Transport Policy, Elsevier, vol. 109(C), pages 48-60.
    10. Pilar Mercader-Moyano & Ana Mª Estable-Reifs & Homero Pellicer, 2021. "Toward the Renewal of the Sustainable Urban Indicators’ System after a Global Health Crisis. Practical Application in Granada, Spain," Energies, MDPI, vol. 14(19), pages 1-43, September.
    11. Andrew C Stokes & Dielle J Lundberg & Irma T Elo & Katherine Hempstead & Jacob Bor & Samuel H Preston, 2021. "COVID-19 and excess mortality in the United States: A county-level analysis," PLOS Medicine, Public Library of Science, vol. 18(5), pages 1-18, May.

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