Socioeconomic and cultural factors driving Human Immunodeficiency Virus epidemic among female sex workers in Akwa-Ibom (South-south) and Benue (North-central) States of Nigeria
Bibliographic record
Abstract
This study was aimed at finding out the socioeconomic and cultural factors driving Human Immunodeficiency Virus infection (HIV) epidemics among Female Sex Workers (FSW) in South-south (Akwa-Ibom) and North-central (Benue) States where the infection prevalence is high in Nigeria. A standardized survey instrument was used in multistage cluster sampling approach in Benue and Akwa-Ibom States using sample size of 415 FSW. The study was done on the classified age brackets between 15 and 49 years with Akwa-Ibom having more participants at 20 to 24 years (32.8%) and Benue at 25 to 29 years (33%). Medical Laboratory Scientists equally carried out three (3) stage HIV testing Algorithm among the FSWs under the study. FSWs were subtyped into Brothel-based Female Sex Workers (BBFSW) and Non-Brothel based Female Sex Workers (NBBFSW). Human Immunodeficiency Virus prevalence in Nigeria from the study is 15.5% with Akwa-Ibom having 11.4% while Benue has 20.2% of their population among Female Sex Workers key population typology respectively. Significant differences exist between the two states in the various socioeconomic factors driving the epidemics among Female Sex Workers. For instance, knowledge of HIV status, knowledge of source of HIV Testing Services (HTS) or medication for Acquired Immunodeficiency Syndrome (AIDS), referrals, knowledge of HIV indicators, their risk perception, knowledge and use of Post-Exposure Prophylaxis (PEP) and Pre-Exposure Prophylaxis (PrEP), stigma and discrimination and age at sexual debut, stigmatization, knowledge, use of PEP and PrEP, inconsistent use of condom, less risk perception and use of alcohol are some of the key factors driving the increased prevalence of HIV among FSW in Akwa-Ibom and Benue States in Nigeria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".