In collaboration with community partners, this study will identify disparities and dynamics of COVID-19 testing and infections in three Texas regions; and implement a multilevel intervention that increases access to testing and referrals to follow-up care among vulnerable populations. Using a three-arm group-randomized controlled trial, this study will assess the impact of multi-level interventions influencing motivation and access to testing. The outcomes of this study are measured at the population level and no individual data will be gathered. Analyses of de-identified PHI data from local and regional health departments on COVID testing and infection rates will be used to assess intervention outcomes.
In the U.S. vulnerable populations experience significant disparities in terms of both COVID-19 infection and mortality rates, especially in Texas, where Hispanic, African Americans, and other groups have experienced substantial disparities in both incidence and mortality. Building on the partnerships and resources of the Center for Clinical and Translational Science (CCTS), the goal of the proposed project is to identify dynamic COVID-19 disease hotspots and testing deserts in racially diverse regions of South Texas, Houston/Harris County, Texas, and Northeast Texas to inform the rapid adaptation and deployment of multilevel level just-in-time adaptive intervention strategies to reduce testing disparities among vulnerable populations. A group-randomized controlled trial (RCT) will be conducted to evaluate the reach, effectiveness, and implementation of a community-level Just-In-Time-Adaptive-Intervention (JITAI) to increase COVID-19 testing in identified high-risk priority neighborhoods. To conduct the RCT, 120 priority census blocks groups will be identified and randomized to each condition using a community risk index score that balances distribution in the three study arms with respect to important characteristics including population density, demographics, and baseline testing rates. In Intervention Condition 1 - Multi-Level Multi-Component Intervention (MLI), individuals will receive a multilevel, multi-component intervention comprising of 1) Building testing access for vulnerable populations, 2) Community Health Worker (CHW)-delivered navigation to COVID-19 testing and access and reinforcing risk mitigation recommendations; 3) 2-1-1 helpline-referrals and navigation to testing and 4) social marketing and small media campaign to provide geo-targeted messages promoting testing and COVID-19 risk mitigation behaviors. In Intervention Condition 2 - Community JITAI individuals will receive the same MLI intervention components but with an added JITAI approach informed by real-time data related to testing and other relevant information based on community and stakeholder experience and tacit knowledge about factors influencing testing determinants. The Comparison Condition will receive standard exposure to ongoing city and county communication and access to testing.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
NONE
Enrollment
1,280
The strategic components of our multi-level, multi-component intervention (MLI) include: 1. Building testing access for vulnerable populations, 2) Community Health Worker (CHW)-delivered navigation to SARSCoV- 2 testing and access and reinforce risk mitigation recommendations, 3) 2-1-1 helpline-referrals and navigation to FDA approved SARSCoV- 2 testing (and self sampling once approved) and risk mitigation education, and 4) social marketing and small media campaign to provide geo-targeted messages promoting testing and COVID risk mitigation behaviors. We selected these components because of their evidence base, their current use by partners in response to COVID 19, and confidence that they can be adapted through a community engaged process as described.
This intervention includes the same MLI components described above, with an added JITAI approach. Community and stakeholder partners will use real-time data related to testing and other relevant information generated by the Epidemiologic Surveillance and Analysis team (ESA) in Aim 1, as well as other information based on their community and stakeholder experience and tacit knowledge about factors influencing testing determinants, to adapt intervention activities as needed to optimize access to testing.
The University of Texas Health Science Center, Brownsville
Brownsville, Texas, United States
The University of Texas Health Science Center at Houston
Houston, Texas, United States
The University of Texas Health Science Center at Tyler
Tyler, Texas, United States
Testing Uptake
Examine the short and long-term change in testing proportion from baseline in the CBGs adjusted for testing capacity (testing proportion in the county during the same time period)
Time frame: Baseline through study completion (26 months)
Disparities in Testing
Explore impact on testing disparities by race/ethnicity and SES
Time frame: Baseline through study completion (26 months)
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