Antenatal hepatitis B screening in Nigeria: A comparative analysis with syphilis and HIV
Bibliographic record
Abstract
Nigeria has adopted routine screening of pregnant women for hepatitis B virus (HBV) as part of the interventions to eliminate its vertical transmission. However, there is a dearth of evidence on the coverage of routine antenatal HBV screening as recommended in the national guidelines. This study examined the antenatal HBV screening rate and the positivity rate compared with syphilis and HIV. We conducted a descriptive analysis of the 2019 national HIV/AIDS health sector data. The study included approximately 2.8 million pregnant women who received antenatal care (ANC) in over 6000 health facilities providing prevention of mother-to-child transmission of HIV services in Nigeria. Of the ANC clients, 0.2 million (7.2%) were screened for HBV. At the zonal level, the South West had the highest HBV screening rate (19%), while the lowest rate was in the North East (2.5%). The percentage of pregnant women screened for HBV was lower than those screened for syphilis (16.3%) and HIV (90.3%). Among those screened for HBV, the positivity rate was 5%. The HBV positivity rate ranged from 8.5% in the North Central zone to 1.3% in the South East zone. The positivity rates for syphilis and HIV were 0.4% and 0.5%, respectively. Our results indicate a low antenatal HBV screening rate and a wide disparity compared with HIV and syphilis. This finding highlights the need to understand and address the barriers affecting routine antenatal HBV screening and to strengthen the integration of HBV services into the HIV program 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".