ArticleFrontiers in public health2022
The Arizona Prevention Research Center partnerships in Arizona to promote COVID-19 vaccine health equity.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Overcoming barriers to vaccination among U.S. farmworkers: a scoping review of targeted interventions and strategies.BMC public health · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
Background: Vaccine hesitancy in the face of the COVID-19 pandemic is a complex issue that undermines our national ability to reduce the burden of the disease and control the pandemic. The COVID-19 pandemic revealed widening health disparities and disproportionate adverse health outcomes in terms of transmission, hospitalizations, morbidity and mortality among Arizona's Latinx rural, underserved, farmworker, disabled and elderly populations. In March 2021, ~8.1% of those vaccinated were Latinx, though Latinxs make up 32% of Arizona's population. The Arizona Vaccine Confidence Network (AzVCN) proposed to leverage the expertise of the Arizona Prevention Research Center (AzPRC) and the resources of the Mel and Enid Zuckerman College of Public Health (MEZCOPH) Mobile Health Unit (MHU) to identify, implement and evaluate a MHU intervention to increase uptake of COVID-19 vaccines. Methods: The AzVCN focused efforts on Latinx, rural, un/underinsured and farmworker communities in the four Arizona border counties that are at greater risk of COVID-19 morbidity and mortality and may have limited access to vaccination and other essential health services. The AzVCN used listening sessions to create a feedback loop with key stakeholders and critical health care workers to validate barriers/enablers and identify solutions to increase vaccination uptake emerging from the network. The AzVCN also implemented a community-based intervention using community health workers (CHWs) based in a MHU to increase knowledge of the COVID-19 vaccines, reduce vaccination hesitancy and increase vaccination uptake among Latinx rural, un/underinsured and farmworker populations in Southern Arizona. Results: AzVCN outcomes include: identification of enablers and barriers of COVID-19 vaccination in the priority populations; identification of strategies and solutions to address vaccine hesitancy and increase vaccine uptake among priority population; and evidence that the proposed solutions being tested through the AzVCN contribute to increased vaccine uptake among the priority populations. Conclusion: Through these efforts the AzPRC contributed to the CDC's Vaccinate with Confidence Strategy by collaborating with CHWs and other key stakeholders to engage directly with communities in identifying and addressing structural and misinformation barriers to vaccine uptake.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.