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P1-S5.15 Contribution of condom breakage to the HIV epidemic among men who have sex with men in Karnataka, India

2011· article· en· W2326473440 on OpenAlexaff
Michael Pickles, Peter Vickerman, J. Bradley, B M Ramesh, Shajy Isac, Reynold Washington, H Prudden, Kirstin Mitchell, Michel Alary, Marie‐Claude Boily

Bibliographic record

VenueSexually Transmitted Infections · 2011
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsMedicineCondomHuman immunodeficiency virus (HIV)Sex workersMen who have sex with menDemographyMale HomosexualityGynecologyVirologySyphilisPopulationEnvironmental healthResearch methodology

Abstract

fetched live from OpenAlex

Background Condom promotion among female sex workers (FSWs) and men who have sex with men (MSM) is one of the key components of the Avahan HIV intervention currently underway in India. High rates of consistent condom use are reported across sites. However, condoms are only effective if they do not break or slip during intercourse, which occur frequently, especially in MSM. Methods We use a deterministic compartmental mathematical model of MSM divided into high and low risk, with average condom use increasing over time, to investigate how breakage influences the course of the epidemic. High-risk MSM (HRMSM) sell sex or have many casual partners, and typically have mostly receptive anal sex. Prior parameter ranges (including condom use) for the model are based on one round of cross-sectional behavioural and biological (IBBA) surveys of HRMSM from four districts in Karnataka state in 2008. In these surveys 16.7% (82/491) of MSM report condom breakage in the last sex act. Condom use increased to 93% by 2008, and was assumed to be constant afterwards. The prior ranges are sampled using Latin hypercube sampling. Model runs that agree with measured HRMSM HIV prevalence (12.7–18.9%) provide the posterior parameter set fitting the data, and are used to make predictions of HIV prevalence with and without condom breakage after the start of the intervention in 2004. Results Abstract P1-S5.15 figure 1 shows change in high/low risk prevalences with and without condom breakage. Even with high rates of condom breakage, HIV prevalence among MSM declines from 16.7% (95% CI 12.7 to 20.8%) in 2004 to 7.9% (5.9 to 9.8%) in HRMSM by 2015. Without condom breakage HIV prevalence declines faster, to 5.6% (4.2 to 6.9%) by 2015. Compared to no condom breakage, there will be 10.3% (10.7%) more cumulative infections with breakage in high-risk (low-risk) MSM from 2004 until 2015. The annual extra fraction of new infections due to condom breakage increases from 4.1% (4.3%), in 2004, to 158.9% (165.3%), in 2015 in high-risk (low-risk) MSM, although the absolute number of infections due to condom breakage decreases as the epidemic is declining and condom use increases. Abstract P1-S5.15 Figure 1 HIV prevalence against time for high-risk MSM (upper curves)and low-risk MSM (lower curves). Shaded region shows 2.5–97.5 percentiles and IQR with breakage. The dashed lines show the 2.5, 97.5 percentiles and quartiles without condom breakage. Conclusions HIV prevalence is projected to decline in MSM in Karnataka, given high rates of reported condom use, even with frequent breakage. However, there will be a large fraction of extra infections due to condom breakage. HIV intervention programmes should examine reasons for high rates of breakage and take steps to address this.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.093
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.002

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 head0.015
GPT teacher head0.284
Teacher spread0.269 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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