Abstract
Background
Prospective cohort studies of SARS-CoV-2 incidence complement case-based surveillance and cross-sectional seroprevalence surveys.
Methods
We estimated the incidence of SARS-CoV-2 infection in a national cohort of 6,738 U.S. adults, enrolled March-August 2020. Using Poisson models, we examined the association of social distancing and a composite epidemiologic risk score with seroconversion. The risk score was created using LASSO regression to identify factors predictive of seroconversion. The selected factors were household crowding, confirmed case in household, indoor dining, gathering with groups ≥ 10, and no masking in gyms/salons.
Results
Among 4,510 individuals with ≥1 serologic test, 323 (7.3%, 95% confidence interval [CI] 6.5%-8.1%) seroconverted by January 2021. Among 3,422 participants seronegative in May-September 2020 and retested during November 2020-January 2021, 161 seroconverted over 1,646 person-years of follow-up (9.8 per 100 person-years [95%CI 8.3-11.5]). Seroincidence rate was lower among females compared to males (IRR: 0.69, 95% CI 0.50-0.94) and higher among Hispanic (IRR: 2.09, 95% CI 1.41-3.05) participants compared to White non-Hispanic. In adjusted models, participants who reported social distancing with people they did not know (IRRalways vs. never: 0.42, 95% CI 0.20-1.0) and with people they knew (IRRalways vs. never 0.64, 95%CI 0.39-1.06; IRRsometimes vs. never 0.60, 95% CI 0.38-0.96) had lower seroconversion risk. Seroconversion risk increased with epidemiologic risk score (IRRmedium vs. low 1.68, 95% CI 1.03-2.81; IRRhigh vs. low 3.49, 95% CI 2.26-5.58). Only 29% of those who seroconverted reported isolating and 19% were asked about contacts.
Conclusion
Modifiable risk factors and poor reach of public health strategies drove SARS-CoV-2 transmission across the U.S.
Keywords: COVID-19, serology, seroconversion, asymptomatic infection, physical distancing, natural history study, epidemiologic study, essential workers, public health interventions, community transmission
Contributor Information
Denis Nash, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA; Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA.
Madhura S. Rane, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
McKaylee M. Robertson, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
Mindy Chang, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Sarah Kulkarni Gorrell, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Rebecca Zimba, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA; Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA.
William You, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Amanda Berry, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Chloe Mirzayi, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA; Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA.
Shivani Kochhar, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA.
Andrew Maroko, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA; Department of Environmental, Occupational, and Geospatial Health Sciences, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA.
Drew A. Westmoreland, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
Angela M. Parcesepe, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA Department of Maternal and Child Health, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, USA; Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Levi Waldron, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA; Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA.
Christian Grov, Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA; Department of Community Health and Social Sciences, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA.
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