Personal Safety during the COVID-19 Pandemic: Realities and Perspectives of Healthcare Workers in Latin America
Bibliographic record
Abstract
Healthcare workers exposed to coronavirus (COVID-19) may not have adequate access to personal protective equipment (PPE), safety procedures, and diagnostic protocols. Our objective was to evaluate the reality and perceptions about personal safety among healthcare workers in Latin America. This is a cross-sectional, online survey-based study administered to 936 healthcare professionals in Latin America from 31 March 2020 to 4 April 2020. A 12-item structured questionnaire was developed. A total of 936 healthcare workers completed the online survey. Of them, 899 (95.1%) were physicians, 28 (2.9%) were nurses, and 18 (1.9%) were allied health professionals. Access to protective equipment was as follows: gel hand sanitizer (n = 889; 95%), disposable gloves (n = 853; 91.1%), disposable gowns (n = 630; 67.3%), disposable surgical masks (785; 83.9%), N95 masks (n = 516; 56.1%), and facial protective shields (n = 305; 32.6%). The vast majority (n = 707; 75.5%) had access to personal safety policies and procedures, and 699 (74.7%) participants had access to diagnostic algorithms. On a 1-to-10 Likert scale, the participants expressed limited human resources support (4.92 ± 0.2; mean ± SD), physical integrity protection in the workplace (5.5 ± 0.1; mean ± SD), and support from public health authorities (5.01 ± 0.12; mean ± SD). Healthcare workers in Latin America had limited access to essential PPE and support from healthcare authorities during the COVID-19 pandemic.
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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 | 0.003 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".