Addressing COVID-19 Testing Disparities in Vulnerable Populations Using a Community JITAI (Just in Time Adaptive Intervention) Approach: RADxUP Phase III

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: 1U01TR004355-01

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2022
    2024
  • Known Financial Commitments (USD)

    $1,096,924
  • Funder

    National Institutes of Health (NIH)
  • Principal Investigator

    ASSISTANT PROFESSOR Cici Bauer
  • Research Location

    United States of America
  • Lead Research Institution

    UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
  • Research Priority Alignment

    N/A
  • Research Category

    Epidemiological studies

  • Research Subcategory

    Impact/ effectiveness of control measures

  • Special Interest Tags

    Data Management and Data Sharing

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Vulnerable populations unspecified

  • Occupations of Interest

    Unspecified

Abstract

Vulnerable populations including those with medical comorbidities, people living in rural settings and minorities experience significant COVID-19 disparities. Additionally, Hispanics and Blacks are significantly more likely to be infected and hospitalized when compared to White, Non-Hispanics. The proposed study builds on RADx-UP Phases I & Phase II work reaching these populations in three racially diverse regions: Houston/Harris County, South Texas, and Northeast Texas to increase SARS-CoV-2 testing, vaccination, and risk mitigation behaviors to reduce COVID-19 morbidity, mortality, and inequities among underserved populations in Texas. The proposed study leverages the partnerships and resources of the Center for Clinical and Translational Science (CCTS) including long-standing community partnerships. Phase III will include mixed methods and community-engaged approaches to inform adaptation of our existing (and the development of new) multilevel intervention messages, materials and strategies with a focus on increasing rapid SARS-CoV-2 testing. It will also include a broader focus on addressing the social determinants of health (SDOH) and an emphasis on combating misinformation. Innovative elements of the proposed study include testing a novel approach to optimize community engagement that uses real-time data to inform intervention adaptation and implementation, using advances in social computing and machine learning to better understand patterns of misinformation in social media, and using multilevel social network analysis techniques to increase intervention agility, intensity, and reach. This project has three aims: Aim 1) Expand existing sources of population-based COVID-19 surveillance data to quantify infection, testing and vaccination trends in three Texas regions, and use innovative methods to inform and evaluate the proposed interventions; Aim 2) Adapt, implement and evaluate the multilevel community just-in-time adaptive intervention (MC-JITAI) developed in Phase II to increase SARS-CoV-2 testing, mitigation behaviors, and COVID-19 vaccination, among underserved and vulnerable populations in three regions of Texas; and Aim 3) Determine the feasibility and effectiveness of leveraging multilevel social networks to improve SARS-CoV-2 testing and COVID-19 vaccination, in three regions of Texas.