CoChat
Sign Up
Cited by 328COVID-19 epidemiological studiesCOVID-19 Clinical Research StudiesUrban and Rural Development Challenges

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

Open access
Ahmad, Khansa, Erqou, Sebhat, Shah, Nishant, Nazir, Umair, Morrison, Alan R., Choudhary, Gaurav, Wu, Wen-Chih·2020·PLOS ONE
DOI 10.1371/journal.pone.0241327PMC PMC7605696

Published version of a preprint

Open this paper in CoChat — free account

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.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0241327

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Residual heightened risk in COVID-19 deaths by lower-income neighbourhoods might reflect a combination of higher exposure risks associated with individual-level occupation and housing conditions not fully captured by area-level measures, and poorer access to and quality of prevention and treatment interventions, including testing and anti-virals.

    “Thus, residual heightened risk in COVID-19 deaths by lower-income neighbourhoods might reflect a combination of higher exposure risks associated with individual-level occupation and housing conditions that are not fully captured by area-level measures, and poorer access to and quality of prevention and treatment interventions, including testing(2,62,63) and anti-virals(64).”

    From Social inequalities in COVID-19 death by area-level income in 11.2 million people in Ontario, Canada: patterns over time and the mediating role of vaccination. (2026) · cites this paper as [64]

    The Results and Discussion (page not available in our copy) link poor housing conditions with higher county-level COVID-19 mortality, including after adjustment for median household income, and discuss housing costs as a barrier to seeking healthcare. The paper does not establish that individual-level occupation or housing exposures explain residual risk in lower-income neighbourhoods, nor does it assess the quality of prevention or treatment or access to testing. The citing sentence attaches a separate citation to anti-virals, so that point is not attributed to this source. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 30

  1. [2]COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) https://coronavirus.jhu.edu/map.html. PMC9432867 36057267
  2. [3]Shim E, Tariq A, Choi W, Lee Y, Chowell G. Transmission potential and severity of COVID-19 in South Korea. Int J Infect Dis. 2020; 93: 339– 44. 10.1016/j.ijid.2020.03.031 32198088 PMC7118661 · DOI
  3. [4]Sanche S, Lin YT, Xu C, Romero-Severson E, Hengartner N, Ke R. High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2. Emerg Infect Dis. 2020; 26(7). 10.3201/eid2607.200282 32255761 PMC7323562 · DOI · Paper page
  4. [5]Biggerstaff M, Cauchemez S, Reed C, Gambhir M, Finelli L. Estimates of the reproduction number for seasonal, pandemic, and zoonotic influenza: a systematic review of the literature. BMC Infect Dis. 2014; 14: 480 10.1186/1471-2334-14-480 25186370 PMC4169819 · DOI
  5. [6]Saez M, Tobias A, Varga D, Barcelo MA. Effectiveness of the measures to flatten the epidemic curve of COVID-19. The case of Spain. Sci Total Environ. 2020; 727: 138761 10.1016/j.scitotenv.2020.138761 32330703 PMC7166106 · DOI
  6. [10]Killingley B, Nguyen-Van-Tam J. Routes of influenza transmission. Influenza Other Respir Viruses. 2013; 7 Suppl 2: 42– 51. 10.1111/irv.12080 24034483 PMC5909391 · DOI
  7. [11]Enarson DA, Beyers N, Zhang LX. The tuberculosis pandemic today: routes of transmission and new target groups. Scand J Infect Dis. 2001; 33(1): 9– 12. 10.1080/003655401750064013 11234990 · DOI
  8. [12]Shereen MA, Khan S, Kazmi A, Bashir N, Siddique R. COVID-19 infection: Origin, transmission, and characteristics of human coronaviruses. J Adv Res. 2020; 24: 91– 8. 32257431 PMC7113610
  9. [13]Kolifarhood G, Aghaali M, Mozafar Saadati H, Taherpour N, Rahimi S, Izadi N, et al Epidemiological and Clinical Aspects of COVID-19; a Narrative Review. Arch Acad Emerg Med. 2020; 8(1): e41 32259130 PMC7117787
  10. [14]WHO Housing and Health Guidelines. WHO Guidelines Approved by the Guidelines Review Committee. Geneva 2018.
  11. [16]Stahre M, VanEenwyk J, Siegel P, Njai R. Housing Insecurity and the Association With Health Outcomes and Unhealthy Behaviors, Washington State, 2011. Prev Chronic Dis. 2015; 12: E109 10.5888/pcd12.140511 26160295 PMC4509099 · DOI
  12. [17]Kottke T, Abariotes A, Spoonheim JB. Access to Affordable Housing Promotes Health and Well-Being and Reduces Hospital Visits. Perm J. 2018; 22: 17– 079. 10.7812/TPP/17-079 29236654 PMC5737920 · DOI
  13. [19]Eric Morath RF. "I Have Bills I Have to Pay.’ Low-Wage Workers Face Brunt of Coronavirus Crisis. The Wall Street Journal. 2020.
  14. [21]Crisanti AS, Duran D, Greene RN, Reno J, Luna-Anderson C, Altschul DB. A longitudinal analysis of peer-delivered permanent supportive housing: Impact of housing on mental and overall health in an ethnically diverse population. Psychol Serv. 2017; 14(2): 141– 53. 10.1037/ser0000135 28481599 · DOI · Paper page
  15. [22]Dunn JR, Hayes MV. Social inequality, population health, and housing: a study of two Vancouver neighborhoods. Soc Sci Med. 2000; 51(4): 563– 87. 10.1016/s0277-9536(99)00496-7 10868671 · DOI
  16. [23]Faludi EG. The effect of population movement on housing as it concerns public health. Can J Public Health. 1960; 51: 146– 9. 13821458
  17. [24]Thomas TK, Ritter T, Bruden D, Bruce M, Byrd K, Goldberger R, et al Impact of providing in-home water service on the rates of infectious diseases: results from four communities in Western Alaska. J Water Health. 2016; 14(1): 132– 41. 10.2166/wh.2015.110 26837837 PMC5557094 · DOI
  18. [25]Lau JT, Lau M, Kim JH, Tsui HY, Tsang T, Wong TW. Probable secondary infections in households of SARS patients in Hong Kong. Emerg Infect Dis. 2004; 10(2): 235– 43. 10.3201/eid1002.030626 15030689 PMC3322902 · DOI
  19. [28]Guan WJ, Liang WH, Zhao Y, Liang HR, Chen ZS, Li YM, et al Comorbidity and its impact on 1590 patients with Covid-19 in China: A Nationwide Analysis. Eur Respir J. 2020 10.1183/13993003.00547-2020 32217650 PMC7098485 · DOI · Paper page
  20. [31]Rimmer A. Covid-19: Disproportionate impact on ethnic minority healthcare workers will be explored by government. BMJ. 2020; 369: m1562 10.1136/bmj.m1562 32303494 · DOI · Paper page
  21. [32]Kim ES, Chin BS, Kang CK, Kim NJ, Kang YM, Choi JP, et al Clinical Course and Outcomes of Patients with Severe Acute Respiratory Syndrome Coronavirus 2 Infection: a Preliminary Report of the First 28 Patients from the Korean Cohort Study on COVID-19. J Korean Med Sci. 2020; 35(13): e142 10.3346/jkms.2020.35.e142 32242348 PMC7131901 · DOI
  22. [34]Lau JT, Lau M, Kim JH, Tsui HY, Tsang T, Wong TW. Probable secondary infections in households of SARS patients in Hong Kong. Emerg Infect Dis. 2004; 10(2): 235– 43. 10.3201/eid1002.030626 15030689 PMC3322902 · DOI
  23. [35]Hua Qian TM, Li LIU, Xiaohong Zheng, Danting Luo, Yuguo Li. Indoor transmission of SARS-CoV-2. 2020. 33131151
  24. [36]Aligne CA. Overcrowding and Mortality During the Influenza Pandemic of 1918. Am J Public Health. 2016; 106(4): 642– 4. 10.2105/AJPH.2015.303018 26959269 PMC4816079 · DOI
  25. [37]Liu Y, Yan LM, Wan L, Xiang TX, Le A, Liu JM, et al Viral dynamics in mild and severe cases of COVID-19. Lancet Infect Dis. 2020 10.1016/S1473-3099(20)30232-2 32199493 PMC7158902 · DOI · Paper page
  26. [38]Team C-I. Clinical and virologic characteristics of the first 12 patients with coronavirus disease 2019 (COVID-19) in the United States. Nat Med. 2020. PMC12755114 32327757
  27. [39]Zheng S, Fan J, Yu F, Feng B, Lou B, Zou Q, et al Viral load dynamics and disease severity in patients infected with SARS-CoV-2 in Zhejiang province, China, January-March 2020: retrospective cohort study. BMJ. 2020; 369: m1443 10.1136/bmj.m1443 32317267 PMC7190077 · DOI
  28. [40]Schiavo R, May Leung M, Brown M. Communicating risk and promoting disease mitigation measures in epidemics and emerging disease settings. Pathog Glob Health. 2014; 108(2): 76– 94. 10.1179/2047773214Y.0000000127 24649867 PMC4005587 · DOI
  29. [43]Bean B, Moore BM, Sterner B, Peterson LR, Gerding DN, Balfour HH. Survival of influenza viruses on environmental surfaces. J Infect Dis. 1982; 146(1): 47– 51. 10.1093/infdis/146.1.47 6282993 · DOI
  30. [45]Mehra MR, Desai SS, Kuy S, Henry TD, Patel AN. Cardiovascular Disease, Drug Therapy, and Mortality in Covid-19. N Engl J Med. 2020. PMC7206931 32356626

Cited by

Sorted by citations

Authors
Ahmad, K., Erqou, S., Shah, N., Nazir, U., Morrison, A. R., Choudhary, G., & Wu, W.-C.
Affiliations
Brown University (US)
Corresponding author
Wu, Wen-Chih
ORCID
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2020-11-02
Volume
15
Issue
11
Pages
e0241327
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0241327
PMC
PMC7605696
OpenAlex
W3095349481
Cited by
328
References
6
Citations by year
2026: 14 · 2025: 16 · 2024: 36 · 2023: 44 · 2022: 92 · 2021: 122 · 2020: 4
FWCI
10.41
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, public-domain)
  • SSRN Electronic Journal (publishedVersion)
  • medRxiv (acceptedVersion, cc-by-nd)
  • PubMed Central (publishedVersion, public-domain)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion, public-domain)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • U.S. Department of Veterans Affairs (I01 HX002422-01A2, I01 HX002422, IK2BX002527, 7IK2BX002527)
  • Rhode Island Foundation
  • National Institutes of Health (NIGMS P20GM103652, NHLBI R01HL139795)
  • Center for AIDS Research, University of Washington
  • National Heart, Lung, and Blood Institute (R01HL139795)
  • National Institute of General Medical Sciences (P20GM103652)
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
  • Social Sciences › Urban Studies › Urban and Rural Development Challenges
Keywords
substandard housing, COVID-19 incidence, COVID-19 mortality, household crowding, housing cost burden, county-level health disparities, social determinants of health, disease transmission, United States counties, population density, health care access, comorbidities, income and education disparities, health insurance
MeSH terms
Betacoronavirus, COVID-19, SARS-CoV-2, Adult, Aged, Cross-Sectional Studies, Family Characteristics, Female, Housing, Humans, Male, Middle Aged, Pneumonia, Viral, Risk, Social Class, United States, Incidence, Coronavirus Infections, Young Adult, Pandemics

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review