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
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».