# Motivate, Vaccinate, Activate’: An effectiveness-implementation trial to assess the impact of a multi-component community-based intervention to increase RSV vaccine uptake among Latino older adults

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $686,134

## Abstract

PROJECT SUMMARY/ABSTRACT
Respiratory Syncytial Virus (RSV) causes a substantial burden of hospitalizations and deaths among older
adults, comparable to that of influenza. The new and effective RSV vaccines have the potential to dramatically
reduce RSV morbidity and mortality, yet their full public health impact will not be realized if the racial and ethnic
disparities in RSV vaccine uptake mirror those observed in other respiratory virus-vaccines, from COVID-19 to
influenza. We have the opportunity to adapt community-based interventions from the COVID-19 pandemic to
proactively address disparities in RSV vaccine uptake. However, evidence-based data, conducted in
partnership with impacted communities, are essential.
This project will focus on increasing RSV vaccine uptake among Latinos, a community disproportionatly
affected by respiratory vaccines and RSV. We will leverage our well-established community-academic
partnership, Unidos en Salud, to adapt two components of our ‘Motivate, Vaccinate, Activate’ intervention—
CHW counseling and text message nudges. This multi-component intervention was originally designed to
increase COVID-19 vaccine uptake among Latinos and to activate people to recommend vaccination to people
in one’s social network. Our overall study objective is to adapt this intervention to inform effective and
customizable community-based strategies to increase RSV vaccine uptake. In addition to a rigorous
randomized trial design, we will collect detailed implementation outcomes to aide in generalizability and
adaption to other vaccines and settings. Our primary hypothesis is that language-and culturally-concordant
CHW motivation and activation counseling sessions, coupled with text message nudges, will increase RSV
vaccine confidence by adressing trust, knowledge, and access-related barriers. The proposed study has three
aims. In Aim 1 we will use the ADAPT-IT framework to adapt two intervention components: CHW counseling
and text-message nudges to increase RSV vaccine uptake among Latino older adults (>60 years) (Aim 1a)
and enable younger adults (18-50 years old) to discuss RSV vaccination with older adults in their social and
family networks (Aim 1b). Then in Aim 2 we will conduct a two-arm type-1 effectiveness implementation trial to
determine the effectiveness and implementation of a CHW counseling and text-message intervention on RSV
vaccine uptake in Latino adults >60 years. In Aim 3, using a parallel trial design and social network analytic
techniques, we will test the effectiveness of CHW counseling and text-message nudges on activating Latino
adults to discuss RSV vaccination with the older adults within their social networks.
The proposed work will provide timely, rigorous, and adaptable data to directly inform community-based
approaches to increase RSV vaccination. In addition to providing timely data to reduce RSV vaccine
disparities, these data will also advance our scientific understanding of the effectiveness of tex...

## Key facts

- **NIH application ID:** 10943906
- **Project number:** 1R01MD019749-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Carina Marquez
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $686,134
- **Award type:** 1
- **Project period:** 2024-08-26 → 2029-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10943906

## Citation

> US National Institutes of Health, RePORTER application 10943906, Motivate, Vaccinate, Activate’: An effectiveness-implementation trial to assess the impact of a multi-component community-based intervention to increase RSV vaccine uptake among Latino older adults (1R01MD019749-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10943906. Licensed CC0.

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