Perceptions of the COVID-19 Vaccine and Willingness to Receive Vaccination among Health Workers in Nigeria: A Cross-sectional Study
Bibliographic record
Abstract
BACKGROUND: COVID-19 vaccine hesitancy is a major barrier to vaccine uptake, and the achievement of herd immunity is required to reduce morbidity and mortality and protect the most vulnerable populations. In Nigeria, COVID-19 vaccine hesitancy has been high, and uptake remains very low. Healthcare workers (HCWs) in Nigeria can help support public health efforts to increase vaccine uptake. AIM: This study evaluates Nigerian HCWs' acceptance and intent to recommend the COVID-19 vaccine. SUBJECTS AND METHODS: Cross-sectional survey among 1,852 HCWs in primary, secondary, and tertiary care settings across Nigeria. Respondents included doctors, nurses, pharmacy workers, and clinical laboratory professionals who have direct clinical contact with patients in various healthcare settings. A 33-item questionnaire was used in the study, with two of the questions focused on the COVID-19 vaccine. The responses to the two questions were analyzed using Chi-square (c2) tests and independent t-tests to determine the acceptance of the vaccine. RESULTS: The majority of respondents were younger than 34 years (n = 1,227; 69.2%) and primarily worked in hospitals (n = 1,278; 72.0%). Among the respondents, 79.2% (n = 1,467) endorsed the COVID-19 vaccine as a critical tool in reducing the impact of the disease, and 76.2% (n = 1,412) will accept and recommend the vaccine to their patients. The younger HCWs were more likely to endorse and recommend the vaccine to their patients. CONCLUSION: There is a moderately high COVID-19 vaccine acceptance rate among HCWs surveyed in our study. The confidence of HCWs in its use and their willingness to recommend it to their patients can provide a potentially useful element in increasing acceptance by the larger population in Nigeria.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".