Organizational Factors Associated with Health Worker Protection: A Participatory Mixed-Method Cross-Sectional Analysis in Four Provinces of South Africa
Bibliographic record
Abstract
Abstract Background: Health workers, in short supply in many low-and-middle-income countries (LMICs), are at increased risk of SARS-CoV-2 infection during their employment. This study aimed to assess how South Africa, an LMIC, prepared to protect its health workers from SARS-CoV-2. Methods: This was a participatory mixed method study conducted in four provinces of South Africa. We used a semi-structured questionnaire and a walkthrough survey to collect data on occupational safety and health (OSH) systems in 45 hospitals across four provinces to identify factors associated with health worker protection. Adapting the International Labour Organization (ILO) and World Health Organization (WHO) HealthWISE tool, we compiled compliance scores through walkthrough surveys. For the questionnaire, the participants were provincial OSH managers. For the walkthrough survey, they were frontline health workers, facility managers, and OSH and Infection Prevention and Control (IPC) professionals. We used logistic regression to analyze the relationship between readiness indicators and the actual implementation of protective measures. We also evaluated the association between OSH compliance and hospital infection rates.Results: We found that health facilities in all four provinces had SARS-CoV-2 plans for the general population but no comprehensive OHS plan for health workers. Province A and D Provincial Department of Health (PDoH) had an OSH SARS-CoV-2 provincial coordinating team and a dedicated budget for occupational health. Province A had an occupational health doctor and an occupational health nurse, while Province B had an occupational health nurse. Province A and D PDoHs had functional OSH committees, and Province D had conducted some health risk assessments specific to SARS-CoV-2. However, none of the assessed health facilities had an acceptable HealthWISE compliance score (≥ 75%) due to poor ventilation and inadequate administrative control measures. While the supply of personal protective equipment (PPE) was adequate, PPE was often not worn properly. Our study found that having an OSH SARS-CoV-2 policy was significantly associated with higher PPE and ventilation scores. In addition, our analysis showed that hospitals with higher compliance scores had significantly lower infection rates (IRR 0.98; 95% CI: 0.97, 0.98).Conclusions: Despite some initial preparedness, greater effort to protect health workers is still warranted. LMICs may need to pay more attention to OSH systems and consider using tools, such as ILO/WHO HealthWISE tool, to protect health workers' health.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".