Tuberculosis among Foreign-born Persons in the United States
Bibliographic record
Abstract
RATIONALE: In the United States, the number of annual reported cases of tuberculosis (TB) among U.S.-born persons declined by 62% from 1993 to 2004, but increased by 5% among foreign-born persons. Over half of all reported cases of TB in the United States occur among foreign-born persons, most of these due to activation of latent TB infection (LTBI). Current guidelines recommend targeting only foreign-born persons who entered the United States within the previous 5 yr for LTBI testing. OBJECTIVE: We sought to assess the epidemiologic basis for this guideline. METHODS: We calculated TB case rates among foreign-born persons, stratified by duration of United States residence and world region of origin. We determined the number of cases using 2004 U.S. TB surveillance data, and calculated case rates using population data from the 2004 American Community Survey. MEASUREMENTS AND MAIN RESULTS: In 2004, a total of 14,517 cases of TB were reported; 3,444 (24%) of these were among foreign-born persons who had entered the United States more than 5 yr previously. The rate of TB disease among foreign-born persons was 21.5/100,000, compared with 2.7/100,000 for U.S.-born persons, and varied by duration of residence and world region of origin. CONCLUSIONS: Almost one-quarter of all TB cases in the United States occur among foreign-born persons who have resided in the United States for longer than 5 yr; case rates for such persons from selected regions of origin remain substantially elevated. To eliminate TB, we must address the burden of LTBI in this high-risk group.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".