ArticleAmerican journal of preventive medicine2021
Subway Ridership, Crowding, or Population Density: Determinants of COVID-19 Infection Rates in New York City.
Article in American journal of preventive medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.
- Effects of the built environment and human factors on the spread of COVID-19: A systematic literature review.The Science of the total environment · 2022Pooled it
- [Geography and health-the example of the COVID-19 pandemic in Bremen].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2025Article
- Spatial analysis of COVID-19 incidence and mortality rates in northwest iran for future epidemic preparedness.Scientific reports · 2025Article
- Analysis on effectiveness of subway epidemic prevention measures considering subway passenger flow.Frontiers in public health · 2025Article
- Compact living or policy inaction? Effects of urban density and lockdown on the COVID-19 outbreak in the US.Urban studies (Edinburgh, Scotland) · 2023Article
- Race, masks, residency and concern regarding COVID-19 transmission.Journal of community psychology · 2023Article
- Influences of obstacle factors on the transmission trends of respiratory infectious diseases in indoor public places.Journal of building engineering · 2023Article
- Do the determinants of COVID-19 transmission differ by epidemic wave? Evidence from U.S. counties.Cities (London, England) · 2022Article
- COVID-19 transmission in cities.European economic review · 2022Article
- Impact of pre-pandemic travel mobility patterns on the spatial diffusion of COVID-19 in South Korea.Journal of transport & health · 2022Article
- A systematic review of COVID-19 transport policies and mitigation strategies around the globe.Transportation research interdisciplinary perspectives · 2022Article
- Neighborhood, built environment and resilience in transportation during the COVID-19 pandemic.Transportation research. Part D, Transport and environment · 2022Article
- The Effect of Strict Lockdown on Omicron SARS-CoV-2 Variant Transmission in Shanghai.Vaccines · 2022Article
- Do social determinants of health explain racial/ethnic disparities in COVID-19 infection?Social science & medicine (1982) · 2022Article
- Predicting COVID-19 Infections in Eswatini Using the Maximum Likelihood Estimation Method.International journal of environmental research and public health · 2022Article
- The emission and dynamics of droplets from human expiratory activities and COVID-19 transmission in public transport system: A review.Building and environment · 2022Review
- Geographies of infections: built environment and COVID-19 pandemic in metropolitan Melbourne.Sustainable cities and society · 2022Article
- Rethinking urban density, vitality and healthy environment in the post-pandemic city: The case of Istanbul.Cities (London, England) · 2022Article
- Comorbidities, sociodemographic factors, and determinants of health on COVID-19 fatalities in the United States.Frontiers in public health · 2022Article
- How COVID-19 reshaped quality of life in cities: A synthesis and implications for urban planning.Land use policy · 2021Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThis study aims to determine whether subway ridership and built environmental factors, such as population density and points of interests, are linked to the per capita COVID-19 infection rate in New York City ZIP codes, after controlling for racial and socioeconomic characteristics.
methodsSpatial lag models were employed to model the cumulative COVID-19 per capita infection rate in New York City ZIP codes (N=177) as of April 1 and May 25, 2020, accounting for the spatial relationships among observations. Both direct and total effects (through spatial relationships) were reported.
resultsThis study distinguished between density and crowding. Crowding (and not density) was associated with the higher infection rate on April 1. Average household size was another significant crowding-related variable in both models. There was no evidence that subway ridership was related to the COVID-19 infection rate. Racial and socioeconomic compositions were among the most significant predictors of spatial variation in COVID-19 per capita infection rates in New York City, even more so than variables such as point-of-interest rates, density, and nursing home bed rates.
conclusionsPoint-of-interest destinations not only could facilitate the spread of virus to other parts of the city (through indirect effects) but also were significantly associated with the higher infection rate in their immediate neighborhoods during the early stages of the pandemic. Policymakers should pay particularly close attention to neighborhoods with a high proportion of crowded households and these destinations during the early stages of pandemics.
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