Epidemiology of exposure to HIV/AIDS risky conditions in healthcare settings: the case of health facilities in Gondar City, North West Ethiopia
Bibliographic record
Abstract
It has been estimated that every year more than quarter a million health care workers exposed to HIV risky conditions in health care settings, more so in developing countries, with high incidence of HIV/AIDS and unsafe practices. Particularly, Sub-Saharan African countries share at least half of these occupational exposures to HIV risky conditions among health care workers. The aim of this study was to determine the epidemiology of health care workers' exposure to HIV/AIDS risky conditions and associated factors in the healthcare settings in Gondar city. Institution based quantitative cross sectional study was conducted from April 1–20, 2014. The study included 401 health care workers who were selected from the source population by simple random sampling technique. Data were collected by interviewing health care workers using structured and pretested questionnaire. After the collected data entered to EPI INFO version 3.5.3 statistical software and exported to SPSS version 20.0 for analysis, both binary and multivariable logistic regressions were done to identify factors associated with exposure to HIV/AIDS risky conditions. From a total of 401 health care workers involved in this study, 162(40.4%) reported at least one history of occupational exposure to HIV/AIDS risky conditions in the last one year. More than half (52.31%) of physicians and 47.62% of anesthetists were exposed to HIV/AIDS risky conditions within one year. Lack of training on infection prevention, 5–10 years work experience, long working hours per week, absence of work guidelines, and dissatisfaction with current job were significantly associated with accidental occupational exposure to HIV/AIDS risky conditions. This study found quite high prevalence of health care workers exposure to HIV/AIDS risky conditions in the health care settings in Gondar city. Therefore, effective and goal oriented educational programmes targeting at health care workers and establishment of surveillance systems for registering, reporting and management of occupational exposures in health care settings are quite important.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".