High prevalence of latent tuberculosis and bloodborne virus infection in a homeless population
Bibliographic record
Abstract
INTRODUCTION: Urban homeless populations in the UK have been shown to have high rates of active tuberculosis, but less is known about the prevalence of latent tuberculosis infection (LTBI). This study aimed to estimate the prevalence of LTBI among individuals using homeless hostels in London. METHODS: We performed a cross-sectional survey with outcome follow-up in homeless hostels in London. Our primary outcome was prevalence of LTBI. Recruitment for the study took place between May 2011 and June 2013. To estimate an LTBI prevalence of 10% with 95% CIs between 8% and 13%, we required 500 participants. RESULTS: 491/804 (61.1%) individuals agreed to be screened. The prevalence of LTBI was 16.5% (81/491; 95% CI 13.2 to 19.8). In UK-born individuals, a history of incarceration was associated with increased risk of LTBI (OR 3.49; 95% CI 1.10 to 11.04; P=0.018) after adjusting for age, length of time spent homeless and illicit drug use. Of the three subjects who met English treatment guidelines for LTBI at the time of the study, none engaged with services after referral for treatment. Prevalence of past hepatitis B infection was 10.4% (51/489; 95% CI 7.7 to 13.1), and 59.5% (291/489; 95% CI 55.1 to 63.9) of individuals were non-immune. Prevalence of current hepatitis C infection was 10.4% (51/489; 95% CI 7.8 to 13.1). CONCLUSIONS: This study demonstrates the high prevalence of LTBI in homeless people in London and the associated poor engagement with care. There is a large unmet need for LTBI and hepatitis C infection treatment, and hepatitis B vaccination, in this group.
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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".