Prevalence of HBsAg and HIV among blood donors in Osogbo, Osun State, Nigeria
Bibliographic record
Abstract
Important among the transfusion transmissible infection are hepatitis B (HBV) and HIV virus infections. Also, co-infection of these two viruses is a rapidly growing issue of public health concern. This study is embarked upon to determine the prevalence these two viruses and their co-infection among blood donors in our environment. HBsAg was detected in each serum sample by means of an immuno-chromatographic mini strip (Clinotech Diagnostics, Richmond, Canada). Antibodies to HIV-1 and 2 were detected in each serum sample by means of an immuno-chromatographic test strip (Abbot Determine HIV 1 and 2, Boehringer, Germany) strictly following the manufacturer’s instructions in all the processes. Of 624 donors screened (age range 18 to 65 years), 124 donors (19.9%) were positive for HBsAg; 19.6% males and 21.0% females (P = 0.7080, 95% CI 0.5654 to 1.493). Twenty one (3%) donors were positive for HIV-1 antibody; 3.4% males and 3.2% females (P=1.000, 95% CI 0.3488-3.196) and 3 donors (0.5%) were positive for combined HBsAg and HIV-1 antibodies, 0.4% males and 3.8% females (P = 0.4861, 95% CI 0.0444 to 5.495). HIV-2 antibody was not detected in any of the sample and there was no invalid result with both the HBsAg and HIV test kits. The result of this study shows that the prevalence of hepatitis B and HIV infections is high among apparently healthy blood donors of all gender and age groups and therefore the need to mandate all organization involved in blood banking to ensure proper screening of blood units prior to transfusion in order to reduce the risk of HBV and HIV infections among recipients of donated blood and the community at large.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".