The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Neighbourhood income and physical distancing during the COVID-19 pandemic in the United States
Open accessPublished version of a preprint
Abstract
Physical distancing has been the primary strategy to control COVID-19 in the United States. We used mobility data from a large, anonymized sample of smartphone users to assess the relationship between neighbourhood income and physical distancing during the pandemic. We found a strong gradient between neighbourhood income and physical distancing. Individuals in high-income neighbourhoods increased their days at home substantially more than individuals in low-income neighbourhoods did. Residents of low-income neighbourhoods were more likely to work outside the home, compared to residents in higher-income neighbourhoods, but were not more likely to visit locations such as supermarkets, parks and hospitals. Finally, we found that state orders were only associated with small increases in staying home in low-income neighbourhoods. Our findings indicate that people in lower-income neighbourhoods have faced barriers to physical distancing, particularly needing to work outside the home, and that state physical distancing policies have not mitigated these disparities.
Overview
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.
Integrity signals
Registry
Cites
Statistics
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
How Much Should We Trust Differences-in-Differences Estimates?
Bertrand, M., Duflo, E., & Mullainathan, S. (2004) · The Quarterly Journal of Economics · doi:10.1162/003355304772839588 · Cited by 10,641
Ferguson, N. M., Laydon, D. J., Nedjati-Gilani, G. L., Imai, N., Ainslie, K. E. C., Baguelin, M., Bhatia, S., Boonyasiri, A., Cucunubá, Z. M., Cuomo-Dannenburg, G., et al. (2020) · Spiral (Imperial College London) · doi:10.25561/77482 · Cited by 3,619
Racial Residential Segregation: A Fundamental Cause of Racial Disparities in Health
Williams, D. R., & Collins, C. (2001) · Public Health Reports · doi:10.1093/phr/116.5.404 · Cited by 3,153
The effect of large-scale anti-contagion policies on the COVID-19 pandemic
Hsiang, S., Allen, D., Annan-Phan, S., Bell, K., Bolliger, I. W., Chong, T., Druckenmiller, H., Huang, L. Y., Hultgren, A., Krasovich, E., et al. (2020) · Nature · doi:10.1038/s41586-020-2404-8 · Cited by 1,528
2013 NCHS Urban-Rural Classification Scheme for Counties.
Ingram, D. D., & Franco, S. J. (2012) · PubMed · Cited by 1,523
Designing Difference in Difference Studies: Best Practices for Public Health Policy Research
Wing, C., Simon, K., & Bello-Gomez, R. A. (2018) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040617-013507 · Cited by 1,470
Eubank, S., Eckstrand, I. A., Lewis, B. L., Venkatramanan, S., MARATHE, M. V., & Barrett, C. L. (2020) · Bulletin of Mathematical Biology · doi:10.1007/s11538-020-00726-x · Cited by 882
Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate
Courtemanche, C., Garuccio, J., Le, A., Pinkston, J. C., & Yelowitz, A. S. (2020) · Health Affairs · doi:10.1377/hlthaff.2020.00608 · Cited by 773
Racial health disparities and covid-19 - caution and context
Chowkwanyun, M., & Reed, A. L. (2020) · New England Journal of Medicine · doi:10.1056/nejmp2012910 · Cited by 706
Massachusetts Department of Public Health
Gallagher, S. S., Guyer, B., Kotelchuck, M., Bass, J. L., Lovejoy, F. H., McLoughlin, E., & Mehta, K. A. (1982) · New England Journal of Medicine · doi:10.1056/nejm198210143071613 · Cited by 591
Research works printed but not linked: 1
- Blau, F. D., Koebe, J. & Meyerhofer P. A. Essential and Frontline Workers in the COVID-19 Crisis (Econofact, 2020); https://econofact.org/essential-and-frontline-workers-in-the-covid-19-crisis · DOI
Cited by
Sorted by citations
Bono, S. A., Villela, E. F. D. M., Siau, C. S., Chen, W. S., Pengpid, S., Hasan, M. T., Sessou, P., Ditekemena, J., Amodan, B. O., Hosseinipour, M. C., et al. (2021) · Vaccines · doi:10.3390/vaccines9050515 · Cited by 350
Environmental Factors Influencing COVID-19 Incidence and Severity
Weaver, A., Head, J. R., Gould, C. F., Carlton, E. J., & Remais, J. V. (2022) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-052120-101420 · Cited by 194
Kim, J., & Kwan, M. (2021) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2021.103039 · Cited by 179
Li, L., Taeihagh, A., & Tan, S. Y. (2023) · Nature Communications · doi:10.1038/s41467-023-36267-9 · Cited by 169
Astell‐Burt, T., & Feng, X. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18052757 · Cited by 137
Metadata
- Authors
- Jay, J., Bor, J., Nsoesie, E. O., Lipson, S. K., Jones, D. K., Galea, S., & Raifman, J.
- Affiliations
- Boston University (US)
- Corresponding author
- Jay, Jonathan
- ORCID
- Venue
- Nature Human Behaviour
- Published
- 2020-11-03
- Volume
- 4
- Issue
- 12
- Pages
- 1294-1302
- ISSN
- 2397-3374 (ISSN-L)
- PMC
- PMC8107986
- OpenAlex
- W3096036142
- Cited by
- 346
- References
- 27
- Citations by year
- 2026: 11 · 2025: 35 · 2024: 46 · 2023: 50 · 2022: 89 · 2021: 103 · 2020: 12
- FWCI
- 10.10
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature Human Behaviour (publishedVersion)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Robert Wood Johnson Foundation (77922)
- National Institutes of Health (UL1TR001430)
- Clinical and Translational Science Institute, Boston University (1UL1TR001430)
- National Institute of Mental Health (K01MH121515)
- National Center for Advancing Translational Sciences
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
- Keywords
- social distancing, COVID-19 pandemic, neighborhood income, socioeconomic disparities, smartphone mobility data, staying at home, work location, low-income neighbourhoods, United States
- MeSH terms
- Teleworking, Physical Distancing, COVID-19, Adult, Employment, Humans, Income, Public Policy, Residence Characteristics, United States
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
