A Multicentre Cross‐Sectional Study on Hepatitis B Vaccination Coverage and Associated Factors Among Personnel Working in Health Facilities in Kumasi, Ghana
Bibliographic record
Abstract
Background: As part of efforts to reach the elimination target by 2030, the WHO and CDC recommend that all HCWs adhere to the three‐dose Hepatitis B vaccination schedule to protect themselves against the infection. This study assessed Hepatitis B vaccination coverage and associated factors among personnel working in health facilities in Kumasi, Ashanti Region, Ghana. Materials and Methods: A cross‐sectional study involving 530 HCWs was conducted in four hospitals in Kumasi from September to November 2023. An investigator‐administered questionnaire was employed in gathering participant demographics and other information related to vaccination coverage. IBM SPSS Version 26.0 and GraphPad Prism 8.0 were used for analysing the data. Results: Even though the majority (70.6%) reported having taken at least one dose of the vaccine, only 43.6% were fully vaccinated (≥ 3 doses). More than a quarter (29.4%) had not taken any dose of the HBV vaccine. Close to a quarter (23.6%) had not screened or tested for HBV infection in their lifetime. The statistically significant variables influencing vaccination status were age, marital status, profession, and status in the hospital. Nearly one‐half (44.9%) of the participants who have not taken the vaccine reported they do not have a reason for not taking it, and a high proportion (80.1%) were willing to take the vaccine when given for free. Conclusion: To combat the low Hepatitis B vaccination coverage among healthcare workers in Kumasi, Ghana, amidst the significant public health threat of HBV infection, comprehensive measures are necessary. These include implementing infection prevention control programmes, enhancing occupational health and safety, and conducting health promotion campaigns in healthcare facilities. Extending and intensifying Hepatitis B screening and vaccination initiatives to tertiary institutions and encouraging employers, supervisors, or team leaders to provide these services nationwide are also recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".