COVID-19 Prevalence, Risk Perceptions, and Preventive Behavior in Asymptomatic Latino Population: A Cross-Sectional Study
Why this work is in the frame
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Bibliographic record
Abstract
Aims To determine the prevalence, level of coronavirus disease 2019 (COVID-19) risk perception attitude and preventive behavior implemented by the Latino population in the United States of America (USA). Methods This cross-sectional study was conducted between July 25 and August 25, 2020, and included asymptomatic Latino participants (n=410) with no current/previous COVID-19 within a religious community in Maryland. Participants answered a questionnaire consisting of three components: patient demographics/socioeconomic status, COVID-19 risk perception, and precautionary behavior. Additionally, a focused history taking and physical examination were performed, and nasal swabs for COVID-19 testing were obtained. Results Around 80% of our study population was 35 years and older, considerably healthy, with only about a third reporting history of chronic disease (~80%); most were females (~66%). Of our participants, 90% lived under poverty; only ~6% had made it to college. When asked about the likelihood of acquiring COVID-19, 97.3% stated they have a low risk of getting infected. However, as we asked about the risk of individuals living in their neighborhood, state, and country, the rates changed to moderate to high (78.4%, 86.3%, and 86.6%, respectively). When asked about preventive behavior, 71.2% stated they never wear masks and 85.4% mentioned they never keep social distance. Additionally, 76 (18.5%) tested positive for COVID-19, whereas 64 (84.2%) developed symptoms at follow-up, 57 (75%) were hospitalized, and 4 (5.2%) died. Conclusions Our study identified inadequate COVID-19 threat perception and lack of engagement in preventive behavior among a group of Latinos living in the USA. We believe that Latino communities across the USA are at markedly high risk of acquiring, spreading, and dying of COVID-19.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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 it