Design of a population-based longitudinal cohort study of SARS-CoV-2 incidence and prevalence among adults in the San Francisco Bay Area

Christina P Lindan; Manisha Desai; Derek Boothroyd; Timothy Judson; Jenna Bollyky; Hannah Sample; Yingjie Weng; Yuteh Cheng; Alex Dahlen; Haley Hedlin; Kevin Grumbach; Jeff Henne; Sergio Garcia; Ralph Gonzales; Charles S Craik; George Rutherford; Yvonne Maldonado

doi:10.1016/j.annepidem.2021.11.001

Design of a population-based longitudinal cohort study of SARS-CoV-2 incidence and prevalence among adults in the San Francisco Bay Area

Ann Epidemiol. 2022 Mar:67:81-100. doi: 10.1016/j.annepidem.2021.11.001. Epub 2021 Nov 17.

Authors

Christina P Lindan¹, Manisha Desai², Derek Boothroyd², Timothy Judson³, Jenna Bollyky⁴, Hannah Sample⁵, Yingjie Weng², Yuteh Cheng⁶, Alex Dahlen⁷, Haley Hedlin², Kevin Grumbach⁸, Jeff Henne⁹, Sergio Garcia⁹, Ralph Gonzales¹⁰, Charles S Craik¹¹, George Rutherford¹², Yvonne Maldonado¹³

Affiliations

¹ Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA; Institute for Global Health Sciences, University of California San Francisco, San Francisco, CA, USA. Electronic address: krysia.lindan@ucsf.edu.
² Quantitative Sciences Unit, School of Medicine, Stanford University, 1070 Arastradero Road, Palo Alto, CA, USA.
³ Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Office of Population Health, University of California San Francisco, Brisbane, CA, USA.
⁴ Division of Primary Care & Population Health, School of Medicine, Stanford University, Stanford, CA, USA.
⁵ Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
⁶ Institute for Scientific Analysis, Alameda, CA, USA; The Henne Group, San Francisco, CA, USA.
⁷ The Chan-Zuckerberg Initiative, Redwood City, CA, USA.
⁸ Department of Family and Community Medicine, University of California San Francisco, San Francisco General Hospital, San Francisco, CA, USA; Office of Population Health, University of California San Francisco, Brisbane, CA, USA.
⁹ Institute for Scientific Analysis, Alameda, CA, USA.
¹⁰ Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
¹¹ Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, USA.
¹² Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA; Institute for Global Health Sciences, University of California San Francisco, San Francisco, CA, USA.
¹³ Department of Pediatrics, School of Medicine, Stanford University, CA, USA.

Abstract

Purpose: We describe the design of a longitudinal cohort study to determine SARS-CoV-2 incidence and prevalence among a population-based sample of adults living in six San Francisco Bay Area counties.

Methods: Using an address-based sample, we stratified households by county and by census-tract risk. Risk strata were determined by using regression models to predict infections by geographic area using census-level sociodemographic and health characteristics. We disproportionately sampled high and medium risk strata, which had smaller population sizes, to improve precision of estimates, and calculated a desired sample size of 3400. Participants were primarily recruited by mail and were followed monthly with PCR testing of nasopharyngeal swabs, testing of venous blood samples for antibodies to SARS-CoV-2 spike and nucleocapsid antigens, and testing of the presence of neutralizing antibodies, with completion of questionnaires about socio-demographics and behavior. Estimates of incidence and prevalence will be weighted by county, risk strata and sociodemographic characteristics of non-responders, and will take into account laboratory test performance.

Results: We enrolled 3842 adults from August to December 2020, and completed follow-up March 31, 2021. We reached target sample sizes within most strata.

Conclusions: Our stratified random sampling design will allow us to recruit a robust general population cohort of adults to determine the incidence of SARS-CoV-2 infection. Identifying risk strata was unique to the design and will help ensure precise estimates, and high-performance testing for presence of virus and antibodies will enable accurate ascertainment of infections.

Keywords: COVID-19; Population-based survey; Probability sample; SARS-CoV-2; SARS-CoV-2 antibody; SARS-CoV-2 viral detection; Surveillance.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Antibodies, Viral
COVID-19* / epidemiology
Cohort Studies
Humans
Incidence
Longitudinal Studies
Prevalence
SARS-CoV-2*
San Francisco / epidemiology

Substances

Antibodies, Viral