Substance use and other factors associated with COVID-19 vaccine uptake among people at risk for or living with HIV: Findings from the C3PNO consortium
Bibliographic record
Abstract
Objective: We describe the prevalence of COVID-19 vaccine uptake, substance use, and other factors associated with vaccine hesitancy among participants from nine North American cohort studies following a diverse group of individuals at risk for or living with HIV. Methods: Between May 2021 and January 2022, participants completed a survey related to COVID-19 vaccination. Participants included those with and without substance use. Those responding as 'no' or 'undecided' to the question "Do you plan on getting the COVID-19 vaccine?" were categorized as vaccine hesitant. Differences between groups were evaluated using chi-square methods and multivariable log-binomial models were used to calculate prevalence ratios (PR) of COVID-19 vaccine hesitancy with separate models for each substance. Results: Among 1,696 participants, COVID-19 vaccination was deferred or declined by 16%. Vaccine hesitant participants were younger, with a greater proportion unstably housed (14.8% vs. 10.0%; p = 0.02), and not living with HIV (48.% vs. 36.6%; p <.01). Vaccine hesitant participants were also more likely to report cannabis (50.0% vs. 42.4%; p = 0.03), methamphetamine (14.0% vs. 8.2%; p <.01), or fentanyl use (5.5% vs. 2.8%; p = 0.03). Based on multivariable analyses methamphetamine or fentanyl use remained associated with COVID-19 vaccine hesitancy (Adjusted PR = 1.4; 95% CI 1.1-1.9 and Adjusted PR = 1.6; 95% CI 1.0-2.6, respectively). Conclusion: As new COVID-19 vaccines and booster schedules become necessary, people who use drugs (PWUD) may remain vaccine hesitant. Strategies to engage hesitant populations such as PWUD will need to be tailored to include special types of outreach such as integration with substance use programs such as safe injection sites or recovery programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".