Factors associated with COVID-19 vaccination in Belize
Bibliographic record
Abstract
Background: We analyzed the factors associated with vaccine uptake, vaccination intention, and reasons for vaccine hesitancy in Belize. Methods: We collected a nationally representative household survey of the population in Belize aged 15 years and older (September-October 2021). We compared potential correlates between vaccinated and unvaccinated people using Chi-square tests. Then, we performed logistic regression analysis to identify factors associated with vaccination uptake among all respondents and vaccination intention among the unvaccinated. Results: Our analysis included data from 1261 interviews. Nearly four out of every five people reported being vaccinated, having received at least one dose. Adolescents and young adults were more likely to be unvaccinated. Significant differences were observed for most behavioral variables. Among the 41.7% of the unvaccinated respondents who said they would probably not or definitely not get vaccinated, the primary reason for their hesitation was fear of side effects. Additionally, almost one third of the unvaccinated individuals expressed a lack of trust in vaccines. Factors associated with increased likelihood of vaccination were efficacy beliefs, self-efficacy and vaccine attitudes. People who believed it was easy to get a vaccine were over 23 times (OR 23.63 [95% CI: 14.21-39.27]) more likely to be vaccinated, while those who believed in vaccine safety were 2.57 times [OR 95% CI: 1.52-4.35] more likely to be vaccinated. Among the unvaccinated, factors associated with intention to get vaccinated were self-identifying as Garifuna and having clear efficacy beliefs. Conclusions: To our knowledge, this is the first study describing factors associated with COVID-19 vaccine uptake and vaccine hesitancy in Belize. Our findings revealed that accessibility has been the primary limitation in increasing vaccine coverage, and <7% of the eligible population have been strong vaccine deniers. To enhance vaccine uptake, targeted outreach efforts are necessary to address access barriers. Our results call for increased efforts improving self-efficacy, efficacy beliefs, and perceived norms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".