Incidence and determinants of tuberculosis among healthcare workers in Free State, South Africa : a historical prospective cohort study and evaluation of infection control
Bibliographic record
Abstract
Healthcare workers (HCWs) are at high-risk of exposure to tuberculosis (TB) at work, yet the incidence rate of TB disease among HCWs in South Africa, and other high-burden countries, is unknown. The effectiveness of TB infection control (IC) measures in South African hospitals remains unclear and evidence examining the relationship between IC and TB among HCWs is lacking. Objective 1: Estimate the incidence rate of TB among HCWs in Free State, South Africa from 2002-2012; and Objective 2: Examine the association between TB IC scores in Free State hospitals and the incidence of TB among HCWs in 2012. A record linkage was conducted to identify HCWs who were registered as TB patients. A historical prospective cohort study was conducted to obtain incidence rate ratios (IRR) of TB among HCWs in Free State from 2002-2012 and to compare patient characteristics. A mixed-effects poisson regression was used to model the association between facility type, occupation, duration of employment, and the rate of TB. A TB IC workplace assessment tool was used in 28 public hospitals. A generalized linear mixed-effects regression was used to assess the association between TB IC scores and incidence of TB among HCWs in 2012. There were 231,834 people diagnosed with TB in Free State from 2002-2012. Among HCWs, 2,677 cases of TB were diagnosed and 1,280 were expected. IRR ranged from 1.14 in 2012 to 3.12 in 2005. HCWs who were older, male, black, coloured and employed less than 20 years had higher risk of TB. There is a large variability in TB IC in Free State. As total IC score, environmental and personal protective equipment (PPE) score increased, the probability of TB among HCWs in that hospital decreased. This study objectively estimates the rate of TB among HCWs in South Africa. The findings confirm that HCWs are at high risk of TB - as much as three-times higher than the population they serve. These findings re-affirm that overall IC and PPE are essential to prevent HCWs from acquiring TB. More attention to TB IC is warranted to protect HCWs and to stop the TB epidemic.
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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 | 0.000 | 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) | 0.000 | 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".