Factors that influence-COVID-19 Vaccine Uptake and Hesitancy Among a Population in the West Department of Haiti: Implications for Enhancing Effectiveness of Immunization Programs
Bibliographic record
Abstract
Abstract Introduction The COVID-19 pandemic in Haiti led to increased challenges for a population concurrently dealing with natural and social disasters, poor quality health care, lack of clean running water, and inadequate housing. While half a million vaccines for COVID-19 were donated by the United States to the government of Haiti, less than 5% of the population agreed to be vaccinated. This resulted in thousands of unused doses that were diverted to other countries. The purpose of this study was to evaluate population characteristics related to vaccine uptake in order to inform future interventions to improve COVID-19 vaccine uptake as well as inform strategies to safeguard against future global health security threats. Methods This was a mixed-methods, cross-sectional study conducted in the West Department of Haiti within peri-urban communes. Survey participants consisted of adults of this setting responding to an electronic survey between June – Sept 2022. The survey assessed demographic information, household characteristics, religious beliefs, past vaccine use, and current COVID-19 vaccine status. Multivariate regression modeling was conducted to assess predictors of vaccine hesitancy. Qualitative focus group discussions were conducted among community leaders and health professionals to provide additional, community-level context on perceptions of the COVID-19 pandemic and vaccines. Results A total of 1,923 respondents completed the survey; of which a majority were male (52.7%), were between the age of 18-35 (58.5%), had a medical visit with the last year (63.0%) and received the COVID-19 vaccine (46.1%). Compared to those who had been COVID-19 vaccinated, participants who had not been vaccinated were more likely to be male (57.7% vs 46.8%, p<.0001), have classical education (30.5% vs 16.6%, p<.001), unemployed (20.3% vs 7.3%, p<.0001) and had a medical visit 3 or more years ago (30.2% vs 11.2%, p<.0001). Unvaccinated COVID-19 participants were also more likely to have never received any other vaccine (36.1% vs22.5%, p<.0001), have a religious leader speak out against the vaccine (20.0% vs 13.1%, p<.0001), not believe in the effectiveness of the vaccine (51.2% vs 9.1%, p<.0001) and did not trust the healthcare worker administering the vaccine (35.2% vs 3.8%, p<0.0001). Conclusion These results show that targeted interventions to religious leaders and health care workers on how to engage with the community and share clearer messages around the COVID-19 vaccination may result in increased vaccine uptake. Results also shed light on how activities surrounding vaccinations can be tailored to meet client needs addressing the misinformation encountered to achieve greater health impact thereby safeguarding the population against future global health security threats.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".