Vaccine-preventable diseases other than tuberculosis, and homelessness: A systematic review of the published literature, 1980 to 2020
Bibliographic record
Abstract
Abstract Background Homelessness may result in the breakdown of regular health services, including routine vaccination programmes. A literature review was conducted to describe vaccine-preventable diseases (VPD) other than tuberculosis in homeless populations and to summarize vaccination recommendations in homeless people. Methods We followed Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. We searched peer-reviewed literature published in English, French or Spanish reporting the outbreak of VPD or VPD prevalence in both infant and adult homeless populations published between 1980 and 2020, using PubMed/Medline, SciELO, Google Scholar, and Web of Science databases. Relevant information from the studies was charted in Microsoft Excel and results were summarised using a descriptive analytical method. Results Seventy-five articles were included. A high prevalence of past HBV and HAV infections were observed through serosurveys, mostly in high income countries or high-middle income countries (USA, Canada, France, Iran or Brazil). Nine outbreaks of HAV infection were also reported, with lethality rates ranging from 0-4.8%. The studies discussed numerous risk factors positively associated with HBV infection, including older age, homosexual or bisexual practice, injected drug use (IDU), and, with HAV infection including IDU, having sexual partner(s) with a history of unspecified hepatitis, insertive anal penetration, or originating from a country with a high prevalence of anti-HAV antibody. Eleven outbreaks of pneumococcal infection affecting homeless persons were reported in Canada and USA, with lethality rates from 0-15.6%. Five diphtheria outbreaks were reported. Vaccination status was rarely documented in these studies. Conclusions The literature suggests that homeless populations generally experience a higher VPD burden and lower immunisation rates. The findings suggest the need for a national vaccination programme and planning for delivering vaccines in this 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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".