Domestic Returns from Investment in the Control of Tuberculosis in Other Countries
Bibliographic record
Abstract
BACKGROUND: We hypothesized that investments to improve the control of tuberculosis in selected high-incidence countries would prove to be cost saving for the United States by reducing the incidence of the disease among migrants. METHODS: Using decision analysis, we estimated tuberculosis-related morbidity, mortality, and costs among legal immigrants and refugees, undocumented migrants, and temporary visitors from Mexico after their entry into the United States. We assessed the current strategy of radiographic screening of legal immigrants plus current tuberculosis-control programs alone and with the addition of either U.S.-funded expansion of the strategy of directly observed treatment, short course (DOTS), in Mexico or tuberculin skin testing to screen legal immigrants from Mexico. We also examined tuberculosis-related outcomes among migrants from Haiti and the Dominican Republic using the same three strategies. RESULTS: As compared with the current strategy, expanding the DOTS program in Mexico at a cost to the United States of 34.9 million dollars would result in 2591 fewer cases of tuberculosis in the United States, with 349 fewer deaths from the disease and net discounted savings of 108 million dollars over a 20-year period. Adding tuberculin skin testing to radiographic screening of legal immigrants from Mexico would result in 401 fewer cases of tuberculosis in the United States but would cost an additional 329 million dollars. Expansion of the DOTS program would remain cost saving even if the initial investment were doubled, if the United States paid for all antituberculosis drugs in Mexico, or if the decline in the incidence of tuberculosis in Mexico was less than projected. A 9.4 million dollars investment to expand the DOTS program in Haiti and the Dominican Republic would result in net U.S. savings of 20 million dollars over a 20-year period. CONCLUSIONS: U.S.-funded efforts to expand the DOTS program in Mexico, Haiti, and the Dominican Republic could reduce tuberculosis-related morbidity and mortality among migrants to the United States, producing net cost savings for the United States.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".