Critical Role of the Subways in the Initial Spread of Sars-CoV-2 in New York City
Bibliographic Data
| ID | 22070267 |
|---|---|
| Authors | Jeffrey E Harris (0000-0002-9749-3205, Massachusetts Institute of Technology, corresponding author) |
| Year | 2021 |
| Volume | 9 |
| Pages | 754767-754767 |
| Publication date | 2021-12-23 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2021.754767 |
| PMID | 35004575 |
| OpenAlex | W4225537080 |
| Language | EN |
| Citations received | 4 |
| References cited | 41 |
We studied the possible role of the subways in the spread of SARS-CoV-2 in New York City during late February and March 2020. Data on cases and hospitalizations, along with phylogenetic analyses of viral isolates, demonstrate rapid community transmission throughout all five boroughs within days. The near collapse of subway ridership during the second week of March was followed within 1–2 weeks by the flattening of COVID-19 incidence curve. We observed persistently high entry into stations located along the subway line serving a principal hotspot of infection in Queens. We used smartphone tracking data to estimate the volume of subway visits originating from each zip code tabulation area (ZCTA). Across ZCTAs, the estimated volume of subway visits on March 16 was strongly predictive of subsequent COVID-19 incidence during April 1–8. In a spatial analysis, we distinguished between the conventional notion of geographic contiguity and a novel notion of contiguity along subway lines. We found that the March 16 subway-visit volume in subway-contiguous ZCTAs had an increasing effect on COVID-19 incidence during April 1–8 as we enlarged the radius of influence up to 5 connected subway stops. By contrast, the March 31 cumulative incidence of COVID-19 in geographically-contiguous ZCTAs had an increasing effect on subsequent COVID-19 incidence as we expanded the radius up to three connected ZCTAs. The combined evidence points to the initial citywide dissemination of SARS-CoV-2 via a subway-based network, followed by percolation of new infections within local hotspots
Cartography · Cohort · Contiguity · Cumulative incidence · Geography · Zip code · Computer Science · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Demography · Human Mobility and Location-Based Analysis · Mathematics · Medicine · Internal Medicine
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Spatial analysis and GIS in the study of Covid-19. A review
Mobility network models of Covid-19 explain inequities and inform reopening
Networks and epidemic models
A Comparison of Infection Venues of Covid-19 Case Clusters in Northeast China
Intergenerational residence patterns and Covid-19 fatalities in the EU and the US
The Role of Subway Travel in an Influenza Epidemic
JUE Insight
| Citations per year | 1 |
|---|---|
| Citation span | 2022 - 2024 (3) |
| Highly cited | No |