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Record W2088561815 · doi:10.1258/ijsa.2008.008128

Cost-effectiveness of voluntary HIV screening in Russia

2008· article· en· W2088561815 on OpenAlexaff
Swati P Tole, Gillian D Sanders, Ahmed M. Bayoumi, Cristina M Galvin, Tatyana Vinichenko, Margaret L. Brandeau, Douglas K Owens

Bibliographic record

VenueInternational Journal of STD & AIDS · 2008
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersNational Institute on Drug AbuseAgency for Healthcare Research and Quality
KeywordsMedicineLife expectancyCost effectivenessQuality-adjusted life yearEnvironmental healthTransmission (telecommunications)Cost–benefit analysisHuman immunodeficiency virus (HIV)DemographyPopulationFamily medicineRisk analysis (engineering)

Abstract

fetched live from OpenAlex

Russia has one of the world's fastest growing HIV epidemics, and HIV screening has been widespread. Whether such screening is an effective use of resources is unclear. We used epidemiologic and economic data from Russia to develop a Markov model to estimate costs, quality of life and survival associated with a voluntary HIV screening programme compared with no screening in Russia. We measured discounted lifetime health-care costs and quality-adjusted life years (QALYs) gained. We varied our inputs in sensitivity analysis. Early identification of HIV through screening provided a substantial benefit to persons with HIV, increasing life expectancy by 2.1 years and 1.7 QALYs. At a base-case prevalence of 1.2%, once-per-lifetime screening cost $13,396 per QALY gained, exclusive of benefit from reduced transmission. Cost-effectiveness of screening remained favourable until prevalence dropped below 0.04%. When HIV-transmission-related costs and benefits were included, once-per-lifetime screening cost $6910 per QALY gained and screening every two years cost $27,696 per QALY gained. An important determinant of the cost-effectiveness of screening was effectiveness of counselling about risk reduction. Early identification of HIV infection through screening in Russia is effective and cost-effective in all but the lowest prevalence groups.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.389
Teacher spread0.325 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2008
Admission routes1
Has abstractyes

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