Authors

  1. Gutierrez-Mock, Luis MA
  2. Burgess, Hailey MPH
  3. Pardo, Seth MPH
  4. Persson, Maceo MPA
  5. Gagliano, Jayne BA
  6. Ho, Y. Xian PhD
  7. Reid, Michael J. A. MD, MPH, MA

Abstract

Objective: To understand how the San Francisco (SF) COVID-19 case investigation and contact tracing (CICT) workforce documented sexual orientation and gender identity (SOGI) data, as well as a qualitative assessment of the workforce's capacity to successfully collect that data.

 

Methods: This mixed-methods project analyzed data from 2 sources: SOGI item completeness among adult completed/partially completed interviews in the SF digital CICT COVID-19 database, and a secondary data analysis of qualitative data from 16 semistructured 90-minute virtual interviews with the SF CICT workforce, between November 14, 2020, and April 14, 2021.

 

Results: Among 15 416 COVID-19 cases and 7836 close contacts, sexual orientation data are missing from 20% of cases and 17% of contacts. The proportion of transgender/nonbinary individuals was 0.32% and 0.5%, respectively. The SF CICTs participants discussed challenges in collecting SOGI data, not understanding SOGI measure rationale, and feeling uncomfortable asking the questions.

 

Conclusion: Qualitative interviews with the COVID-19 CICT workforce and quantitative data on SOGI parameters in COVID-19 surveillance suggest that these data may have been underreported. Our results strongly suggest that comprehensive training is crucial in the collection of SOGI data among COVID-19 cases and their close contacts. If SOGI data are not collected accurately, the true impact of COVID-19 among lesbian, gay, bisexual, transgender, and queer populations remains unknown, preventing data-driven allocation of COVID-19 funds to lesbian, gay, bisexual, transgender, and queer communities.