Responding to pandemics and other disease outbreaks in homeless populations: A review of the literature and content analysis
Bibliographic record
Abstract
Considering the recent COVID-19 pandemic, we recognised a lack of synthesis amongst the available literature pertaining to the intersections of homelessness and pandemic response and planning. Therefore, the purpose of this review was to identify relevant peer-reviewed literature in this area to thematically produce evidence-based recommendations that would inform community planning and response amongst homeless populations. Although this review is inspired by the COVID-19 pandemic, our intention was to produce relevant recommendations to for all current and future outbreaks and pandemics more generally. Our search criteria focused on pandemics and rapid-spread illnesses such as contagious respiratory diseases with contact spread and with an emphasis on individuals experiencing homelessness. Content analysis methods were followed to extract and thematically synthesise key information amongst the 223 articles that matched our search criteria between the years of 1984 and 2020. Two reviewers were assigned to the screening process and used Covidence and undertook two rounds of discussion to identify and finalise themes for extraction. This review illustrates that the current breadth of academic literature on homeless populations has thus far focused on tuberculosis (TB) rather than diseases that are more recent and closely related to COVID-19-such as Severe Acute Respiratory Syndrome (SARS) or H1N1. Our thematic content analysis revealed six themes that offer tangible and scalable recommendations which include (1) education and outreach, (2) adapting structure of services, (3) screening and contract tracing, (4) transmission and prevention strategies, (5) shelter protocols and (6) treatment, adherence and vaccination. The breadth and depth of reviews such as these are dependent on the quantity and quality of the available literature. Therefore, the limited existing literature outside of tuberculosis specific to homelessness in this review illustrates a need for more academic research into the intersections of pandemics and homelessness-particularly for evaluations of response and planning. Nonetheless, this review offers timely considerations for pandemic response and planning amongst homeless populations during the current COVID-19 pandemic and can facilitate future research in this area.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".