Infectious Diseases Among People Experiencing Homelessness: A Systematic Review of the Literature in the United States and Canada, 2003-2022
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Homelessness increases the risk of acquiring an infectious disease. We conducted a systematic review of the literature to identify quantitative data related to infectious diseases and homelessness. We searched Google Scholar, PubMed, and SCOPUS for quantitative literature published from January 2003 through December 2022 in English from the United States and Canada. We excluded literature on vaccine-preventable diseases and HIV because these diseases were recently reviewed. Of the 250 articles that met inclusion criteria, more than half were on hepatitis C virus or Mycobacterium tuberculosis. Other articles were on COVID-19, respiratory syncytial virus, Staphylococcus aureus, group A Streptococcus, mpox (formerly monkeypox), 5 sexually transmitted infections, and gastrointestinal or vectorborne pathogens. Most studies showed higher prevalence, incidence, or measures of risk for infectious diseases among people experiencing homelessness as compared with people who are housed or the general population. Although having increased published data that quantify the infectious disease risks of homelessness is encouraging, many pathogens that are known to affect people globally who are not housed have not been evaluated in the United States or Canada. Future studies should focus on additional pathogens and factors leading to a disproportionately high incidence and prevalence of infectious diseases among people experiencing homelessness.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| 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 it