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Record W2074472927 · doi:10.1177/0956462413500242

Prevalence of HIV, human papillomavirus type 16 and herpes simplex virus type 2 among female sex workers in Guinea and associated factors

2013· article· en· W2074472927 on OpenAlexaff
Joséphine Aho, Anita Koushik, François Coutlée, Soumaila Diakité, Sélim Rashed

Bibliographic record

VenueInternational Journal of STD & AIDS · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicineChlamydia trachomatisSexually transmitted diseaseHerpes simplex virusNeisseria gonorrhoeaePopulationChlamydiaGonorrheaImmunologyVirologyHuman immunodeficiency virus (HIV)Environmental healthVirusSyphilisBiology

Abstract

fetched live from OpenAlex

Female sex workers are at high risk for HIV infection. Sexually transmitted infections are known to be co-factors for HIV infection. Our aims were (1) to assess the prevalence of HIV and other sexually transmitted infections in this population; (2) to determine the association between sociodemographic characteristics, behavioural variables, and variables related to HIV prevention and HIV infection. A cross-sectional study was conducted in Conakry, Guinea, among a convenience sample of 223 female sex workers. A questionnaire on sociodemographic characteristics, risk factors, and exposure to prevention was administered. Screening for HIV, herpes simplex virus type 2, human papillomavirus type 16, Neisseria gonorrhoeae, and Chlamydia trachomatis was performed. Prevalences of HIV, herpes simplex virus type 2, human papillomavirus type 16, N. gonorrhoeae, and C. trachomatis were 35.3%, 84.1%, 12.2%, 9.0%, and 13.6%, respectively. Having a child, lubricant use, and human papillomavirus type 16 infection were associated with HIV infection. Interventions that promote screening and treatment of sexually transmitted infections are needed in order to achieve successful interventions to prevent HIV among female sex workers in resource-limited settings.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.024
GPT teacher head0.321
Teacher spread0.297 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of STD & AIDSSame topicSex work and related issuesFrench-language works237,207