What We (Don’t) Know About the Infectious Disease Burden Among Youth Experiencing Homelessness in the United States and Canada
Bibliographic record
Abstract
Youth experiencing homelessness (YEH) and sexual and gender minority (SGM) YEH may be at increased risk for infectious diseases due to living arrangements, risk behaviors, and barriers to health care access that are dissimilar to those of housed youth and older adults experiencing homelessness. Here, we synthesize findings from 12 peer-reviewed articles published between 2012 and 2020 that enumerate YEH or SGM YEH infectious disease burden in locations across the United States or Canada. Pathogens presented in the reviewed studies were limited to sexually transmitted infections (STIs) and bloodborne infections (BBI). Only 3 studies enumerated infectious diseases among SGM YEH. There was a dearth of comparison data by housing status or SGM identity. We also introduce 3 publicly available surveillance datasets from the United States or Canada that quantify certain STIs, BBIs, and tuberculosis among YEH to support future analyses. Our review calls for more comprehensive YEH-centered research and surveillence to improve estimates of infectious diseases among this vulnerable population.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".