ArticleScientific reports2021
Spatiotemporal contact density explains the disparity of COVID-19 spread in urban neighborhoods.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- 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
- Mobile phone data analyses for public health research: a scoping review.Frontiers in public health · 2025Article
- Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States.Tropical medicine and infectious disease · 2023Article
- Behavioral changes during the COVID-19 pandemic decreased income diversity of urban encounters.Nature communications · 2023Article
- Revealing geographic transmission pattern of COVID-19 using neighborhood-level simulation with human mobility data and SEIR model: A case study of South Carolina.International journal of applied earth observation and geoinformation : ITC journal · 2023Article
- The association of families' socioeconomic and demographic characteristics with parents' perceived barriers to returning to youth sport following the COVID-19 pandemic.Psychology of sport and exercise · 2023Article
- Do the determinants of COVID-19 transmission differ by epidemic wave? Evidence from U.S. counties.Cities (London, England) · 2022Article
- Human activity and mobility data reveal disparities in exposure risk reduction indicators among socially vulnerable populations during COVID-19 for five U.S. metropolitan cities.Scientific reports · 2022Article
- Spatio-temporal distribution pattern of COVID-19 in the Northern Italy during the first-wave scenario: The role of the highway network.Transportation research interdisciplinary perspectives · 2022Article
- Revealing geographic transmission pattern of COVID-19 using neighborhood-level simulation with human mobility data and SEIR model: A Case Study of South Carolina.medRxiv : the preprint server for health sciences · 2022Article
- Perceptions of COVID-19 self-testing and recommendations for implementation and scale-up among Black/African Americans: implications for the COVID-19 STEP project.BMC public health · 2022Article
- Modelling epidemic spread in cities using public transportation as a proxy for generalized mobility trends.Scientific reports · 2022Article
- SARS-CoV-2 monitoring at three sewersheds of different scales and complexity demonstrates distinctive relationships between wastewater measurements and COVID-19 case data.The Science of the total environment · 2022Article
- Perceptions of COVID-19 Self-Testing and Recommendations for Implementation and Scale up Among Black/African Americans: Implications for the COVID-19 STEP Project.Research square · 2022Article
- Effectiveness of wireless emergency alerts for social distancing against COVID-19 in Korea.Scientific reports · 2022Article
- Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review.International journal of public health · 2022Article
- Factors associated with COVID-19 mortality in municipalities in the state of São Paulo (Brazil): an ecological study.Revista da Sociedade Brasileira de Medicina Tropical · 2022Article
Corrections and comments
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Authors and funding
3 authors.
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Abstract
The rapid early spread of COVID-19 in the US was experienced very differently by different socioeconomic groups and business industries. In this study, we study aggregate mobility patterns of New York City and Chicago to identify the relationship between the amount of interpersonal contact between people in urban neighborhoods and the disparity in the growth of positive cases among these groups. We introduce an aggregate spatiotemporal contact density index (CDI) to measure the strength of this interpersonal contact using mobility data collected from mobile phones, and combine it with social distancing metrics to show its effect on positive case growth. With the help of structural equations modeling, we find that the effect of CDI on case growth was consistently positive and that it remained consistently higher in lower-income neighborhoods, suggesting a causal path of income on case growth via CDI. Using the CDI, schools and restaurants are identified as high contact density industries, and the estimation suggests that implementing specific mobility restrictions on these point-of-interest categories is most effective. This analysis can be useful in providing insights for government officials targeting specific population groups and businesses to reduce infection spread as reopening efforts continue to expand across the nation.
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