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Record W4405114387 · doi:10.1097/qco.0000000000001081

Climate change and extreme weather events and linkages with HIV outcomes: recent advances and ways forward

2024· review· en· W4405114387 on OpenAlexafffund
Carmen H. Logie, Andie MacNeil

Bibliographic record

VenueCurrent Opinion in Infectious Diseases · 2024
Typereview
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUnited Nations University Institute for Water, Environment, and HealthWomen's College HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs
KeywordsMedicineTransactional sexContext (archaeology)Mental healthIntrapersonal communicationPreparednessGerontologyInterpersonal communicationEnvironmental healthPsychiatryPsychologyPopulationSocial psychology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Discuss the recent evidence on climate change and related extreme weather events (EWE) and linkages with HIV prevention and care outcomes. RECENT FINDINGS: We identified 22 studies exploring HIV prevention and care in the context of EWE. HIV prevention studies examined sexual practices that increase HIV exposure (e.g., condomless sex, transactional sex), HIV testing, and HIV recent infections and prevalence. HIV care-related outcomes among people with HIV included clinical outcomes (e.g., viral load), antiretroviral therapy adherence and access, HIV care engagement and retention, and mental and physical wellbeing. Pathways from EWE to HIV prevention and care included: structural impacts (e.g., health infrastructure damage); resource insecurities (e.g., food insecurity-related ART adherence barriers); migration and displacement (e.g., reduced access to HIV services); and intrapersonal and interpersonal impacts (e.g., mental health challenges, reduced social support). SUMMARY: Studies recommended multilevel strategies for HIV care in the context of EWE, including at the structural-level (e.g. food security programs), health institution-level (e.g., long-lasting ART), community-level (e.g. collective water management), and individual-level (e.g., coping skills). Climate-informed HIV prevention research is needed. Integration of EWE emergency and disaster preparedness and HIV services offers new opportunities for optimizing HIV prevention and care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.188
GPT teacher head0.402
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations9
Published2024
Admission routes2
Has abstractyes

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