Partner number and use of COVID-19 risk reduction strategies during initial phases of the pandemic in British Columbia, Canada: a survey of sexual health service clients
Bibliographic record
Abstract
OBJECTIVES: Initial public health guidance related to sex and COVID-19 infection focused on reducing partner number. We characterized individuals having a higher partner number during the initial phases of the pandemic. METHODS: In British Columbia, the initial wave of COVID-19 cases was from March 14 to May 19, 2020, followed by gradual lifting of public health restrictions. We conducted an e-mail survey of existing sexual health service clients during the period of July 23 to August 4, 2020. We used bivariate logistic regression to examine the association between the reported number of sexual partners since the start of the pandemic and key variables (level of significance p < 0.01). RESULTS: Of the 1196 clients in our final sample, 42% reported 2+ partners since the start of the pandemic, with higher odds among participants who were men who have sex with men, and single or in open relationships prior to the pandemic. This group was more likely to perceive stigma associated with having sex during the pandemic, and had the highest use of strategies to reduce risk of COVID-19 infection during sexual encounters (mainly focused on reducing/avoiding partners, such as masturbation, limiting sex to a "bubble", and not having sex). CONCLUSION: Sexual health service clients in BC with 2+ partners during the initial phases of BC's pandemic used strategies to reduce their risk of COVID-19 infection during sex. Our study provides support for a harm reduction approach to guidance on COVID-19 risk during sex, and highlights the need for further research on stigma related to having sex during the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".