Analysis of Occupational Infections among Health Care Workers in Limpopo Province of South Africa
Bibliographic record
Abstract
OBJECTIVE: Occupational infections particularly hospital-acquired infections (HAIs) are a serious problem in the healthcare industry worldwide. This study purported to investigate their prevalence and risk factors among healthcare workers from Limpopo province of South Africa. METHODS: Cases about occupational infectious diseases of healthcare workers from Limpopo province that were submitted to the Compensation Commissioner from January 2006 to December 2009 were reviewed. RESULTS: The total number of cases of infectious diseases reported during the study period was 56; of these, 83.9% (47) of cases were for tuberculosis, 10.7% (6) for cholera, and 5.4% (3) for chickenpox. Nurses were the most affected. Risk factors associated with the acquisition of infection diseases were as follows. The majority of those infected were female (67.9%), aged over 40 years (57.1%), and who had worked for over 10 years (59.2%). With regard to length of time it took for one to be infected, overall it took 13.6±9.7 years from the year of employment to being infected. This duration was just 5.7±4.2 years in HCWs younger than 40 years versus 18.4±9.0 years in those 40 years and over (p=0.001); and 11.4±10.3 years in nurses versus 17.1±7.8 years in non-professional staff members (p=0.046). Mopani district, situated in a rural setting was the most affected as 24 of the 47 cases of tuberculosis occurred there. CONCLUSION: In conclusion, the most common occupational infection or hospital acquired infection among healthcare workers in Limpopo province of South Africa was tuberculosis. It infected mainly nurses from the rural health district of Mopani. Younger age and being a nurse were significant risk factors associated with being infected early.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".