A biosocial approach to understanding SARS-CoV-2 seroprevalence in an Orthodox Jewish community
Bibliographic record
Abstract
<h2>Abstract</h2> Identity-based and religious minority groups have been disproportionately affected by the SARS-CoV-2 virus globally. The Montreal Orthodox Jewish community suffered high morbidity and mortality compared to the rest of the Canadian population. As a bounded and exclusive ethnic group, they experienced vulnerabilities related to residence patterns, livelihood and religious practices, encounters with the state, and visibility, characteristics which they share with other minority groups. Here, we interrogate biosocial factors associated with seroprevalence. We used a parallel convergent mixed methods approach comprising blood sampling with concurrent surveying, and semi-structured interviews with a subset of study participants. Participants were recruited between June 23, 2021 and May 25, 2022. Adults were eligible to participate throughout the recruitment period, while adolescents aged 12–17 years and children aged under 12 years became eligible to participate beginning in August 2021 and early February 2022 respectively. Serological testing was done with a multiplex assay for SARS-CoV-2 IgG antibodies. A total of 252 individuals were recruited over a period of 11 months with an overall seroprevalence of 42.5 %. Higher SARS-CoV-2 seroprevalence in the target group, compared to the Canadian national average, is attributed to biosocial factors affecting transmission, including cultural beliefs and practices, and lack of trust in state authorities. The differential impact of infectious disease on minority populations needs to be addressed in socio-culturally and contextually relevant ways to develop successful prevention and mitigation strategies that reduce both transmission and the suffering that accompanies infection.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".