4.6 Article

Population density and basic reproductive number of COVID-19 across United States counties

Journal

PLOS ONE
Volume 16, Issue 4, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0249271

Keywords

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Funding

  1. United States Agency for International Development (USAID) [AID-OAA-A-15-00070]
  2. NIH [R01 GM122876]

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The study found that there is an association between population density and R-0 of SARS-CoV-2, with higher population density counties having higher transmission rates. A population density threshold of 22 people/km(2) was needed to sustain an outbreak, and each increase in one unit of log population density increased R-0 by 0.16.
The basic reproductive number (R-0) is a function of contact rates among individuals, transmission probability, and duration of infectiousness. We sought to determine the association between population density and R-0 of SARS-CoV-2 across U.S. counties. We conducted a cross-sectional analysis using linear mixed models with random intercept and fixed slopes to assess the association of population density and R-0, and controlled for state-level effects using random intercepts. We also assessed whether the association was differential across county-level main mode of transportation percentage as a proxy for transportation accessibility, and adjusted for median household income. The median R-0 among the United States counties was 1.66 (IQR: 1.35-2.11). A population density threshold of 22 people/km(2) was needed to sustain an outbreak. Counties with greater population density have greater rates of transmission of SARS-CoV-2, likely due to increased contact rates in areas with greater density. An increase in one unit of log population density increased R-0 by 0.16 (95% CI: 0.13 to 0.19). This association remained when adjusted for main mode of transportation and household income. The effect of population density on R-0 was not modified by transportation mode. Our findings suggest that dense areas increase contact rates necessary for disease transmission. SARS-CoV-2 R-0 estimates need to consider this geographic variability for proper planning and resource allocation, particularly as epidemics newly emerge and old outbreaks resurge.

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