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Design of a population-based longitudinal cohort study of SARS-CoV-2 incidence and prevalence among adults in the San Francisco Bay Area.
Lindan, Christina P; Desai, Manisha; Boothroyd, Derek; Judson, Timothy; Bollyky, Jenna; Sample, Hannah; Weng, Yingjie; Cheng, Yuteh; Dahlen, Alex; Hedlin, Haley; Grumbach, Kevin; Henne, Jeff; Garcia, Sergio; Gonzales, Ralph; Craik, Charles S; Rutherford, George; Maldonado, Yvonne.
  • Lindan CP; 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.
  • Desai M; Quantitative Sciences Unit, School of Medicine, Stanford University, 1070 Arastradero Road, Palo Alto, CA, USA.
  • Boothroyd D; Quantitative Sciences Unit, School of Medicine, Stanford University, 1070 Arastradero Road, Palo Alto, CA, USA.
  • Judson T; Department of Medicine, University of California San Francisco, San Francisco, CA, USA; Office of Population Health, University of California San Francisco, Brisbane, CA, USA.
  • Bollyky J; Division of Primary Care & Population Health, School of Medicine, Stanford University, Stanford, CA, USA.
  • Sample H; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
  • Weng Y; Quantitative Sciences Unit, School of Medicine, Stanford University, 1070 Arastradero Road, Palo Alto, CA, USA.
  • Cheng Y; Institute for Scientific Analysis, Alameda, CA, USA; The Henne Group, San Francisco, CA, USA.
  • Dahlen A; The Chan-Zuckerberg Initiative, Redwood City, CA, USA.
  • Hedlin H; Quantitative Sciences Unit, School of Medicine, Stanford University, 1070 Arastradero Road, Palo Alto, CA, USA.
  • Grumbach K; 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.
  • Henne J; Institute for Scientific Analysis, Alameda, CA, USA.
  • Garcia S; Institute for Scientific Analysis, Alameda, CA, USA.
  • Gonzales R; Department of Medicine, University of California San Francisco, San Francisco, CA, USA.
  • Craik CS; Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, USA.
  • Rutherford G; 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.
  • Maldonado Y; Department of Pediatrics, School of Medicine, Stanford University, CA, USA.
Ann Epidemiol ; 67: 81-100, 2022 03.
Article in English | MEDLINE | ID: covidwho-1517026
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Limits: Adult / Humans Country/Region as subject: North America Language: English Journal: Ann Epidemiol Journal subject: Epidemiology Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Limits: Adult / Humans Country/Region as subject: North America Language: English Journal: Ann Epidemiol Journal subject: Epidemiology Year: 2022 Document Type: Article