CORRELATES OF COVID VACCINATION UPTAKE AMONG ADULTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS: EMERGING FINDINGS FROM THE 2024-25 RESPIRATORY VIRUS SEASON
Bibliographic record
Abstract
PV079 / #745 Poster Topic: AS11 - Epidemiology and Public Health Background/Purpose People with systemic lupus erythematosus (SLE) are considered more susceptible to COVID; those who become infected may also experience greater severity and disease consequences. COVID vaccination among people with autoimmune diseases is a public health priority. The current study identifies correlates of uptake of the 2024-25 COVID vaccine formulation among people with SLE. Methods Participants were adults 18 years of age and older diagnosed with SLE who live, work, or seek care in Alabama, Louisiana, and Mississippi recruited between August 23, 2024, and January26, 2025 as part of an ongoing study (n=122). Multivariable logistic regression was used to examine 2024-25 COVID vaccination assessed through self-report. Results Approximately 18% of participants (n=22) reported receiving the most recent COVID vaccine. Satterthwaite t-tests revealed that those reporting more barriers to accessing healthcare—lack of transportation, greater distance, competing demands (work, family), cost, and inadequate insurance—were less likely to report receiving the most recent COVID vaccine (t=3.3, 53.4 df, p<0.01). Similarly, reporting barriers within medical contexts—dislike of their hospital, wait times, confusion with the healthcare system, distrust of their doctor, not feeling listened by their doctor, not believing in the efficacy of treatment, and worry about what would happen at the appointment—was associated with lower self-reported vaccination (t=2.1, 59.6 df, p<0.05). Older age was associated with greater reports of vaccination (t=-2.9, 27.2 df, p<0.01). Multivariable logistic regression models were specified, including barriers to access, medical care barriers, demographic (age, race, relationship status), socioeconomic (income, education, work status), and health characteristics (years since SLE diagnosis, organ damage), as well the time of assessment. In this model, barriers to access (OR 0.4, 95% CI 0.2-1.0, p=0.06) and age (OR 1.1, 95% CI 1.0, 1.1, p=0.5) were associated with COVID vaccination at the trend level. Timing of participant assessment was significant at the p=0.07 level (chi-square 7.1, 3 df). As expected, compared to those assessed in October and earlier, those who participated in subsequent months had greater odds of reporting vaccination, but in a nonlinear fashion (November: OR 4.1; December: OR 37.1; January: OR 17.4). Self-reported vaccination was lower in January compared to December, suggesting that vaccination may taper during this time period. Conclusions This study presents recent findings on uptake of the 2024-25 COVID vaccine among adults with SLE. Results suggest that lessening healthcare barriers, particularly those associated with access such as structural challenges, concerns about cost, and multiple role responsibilities, may facilitate COVID vaccination in this population. Efforts to promote COVID vaccination in the time preceding the release of updated formulations may enhance uptake in earlier months, where we saw the lowest reports of vaccination. We found that self-reported vaccination was lower in January compared to December in our sample, suggesting that continued campaigning in later months of the respiratory virus season may be warranted.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".