1861. Prevalence of COVID-19 within Predominantly Black Church Congregations in Ontario, Canada
Bibliographic record
Abstract
Abstract Background Seroprevalence data provide useful information on COVID-19 burden among various communities by detecting infection in both symptomatic and asymptomatic persons. One challenge is the extent to which potential participants agree to blood testing. To address this, we conducted a community-based survey to assess infection rates within church congregations to understand COVID-19 prevalence in a closed group setting in contrast to a conventional open community setting. Methods A cross-sectional survey was conducted within church congregations consisting of mainly Black members from 09/2022 to 05/2023 in Ontario, Canada. Participants completed the survey in person or online. Demographic data and COVID-19-related information, such as polymerase chain reaction (PCR) or rapid antigen positivity and vaccination status, were collected. Survey data were compared with seroprevalence data collected in a related study. Results The survey was completed by 434 persons from 5 different congregations. Male to female ratio 1:2.6. Most participants, 319 (73.5%) completed the survey on paper, in person. The remaining surveys were completed online. Among persons who provided information on age, 50 (12%) survey respondents were 18-30 years of age, 90 (21%) were 31-45, 163 (38%) were 46-60, and 121 (29%) were above 60 years of age. Across all congregations, 46.1% (200/434; 95% CI 41.3-50.9%) reported that they thought they had COVID-19, compared with 39.4% (171/434; 95% CI 34.7-44.1%) who reported testing positive for COVID-19. Among all participants, 9% (40/434) did not receive the COVID-19 vaccine while 88.7% (385/434) completed their primary vaccine series. Seroprevalence data collected by our team revealed a seropositivity rate of up to 80% for the area where most participants reside or work. Among a subset of persons providing both seroprevalence and survey data, there was concordance in approximately 62% (8/13) of seropositive cases. Conclusion The data suggest infection rates reported by a relatively highly vaccinated group of predominantly Black congregants were below that of the general community. Further analyses will examine reasons for these findings. Disclosures All Authors: No reported disclosures
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".