Cost-effectiveness of tuberculosis control strategies among immigrants and refugees
Bibliographic record
Abstract
Today, in Western Europe, Canada and the USA, more than half of all new active tuberculosis (TB) cases occur among foreign-born migrants. This article examines the impact of migration from high TB-incidence to low TB-incidence countries, and compares the cost-effectiveness of different TB control strategies. A Medline search was conducted to identify relevant English language publications prior to December 2003. Additional articles were identified from the reference lists from these publications. Despite the high proportion of active cases in low-incidence countries attributable to foreign-born residents, the public health impact is relatively low. Current chest radiograph screening programmes have little impact and are not cost-effective. Screening with sputum culture would improve cost-effectiveness marginally. Treatment of latent infection detected through screening with tuberculin skin testing or chest radiographs may require coercive measures to maximise impact and cost-effectiveness. In contrast, contact tracing, particularly within ethnic communities, appears to be more cost-efficient and less intrusive. In low-incidence countries, screening of migrants at entry has little overall impact and is not a very cost-effective tuberculosis control strategy. More effective alternatives include contact tracing delivered through primary care and increased investment in global tuberculosis control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".