dbGaP Study Accession: phs002825

NIH Institute/Center: NICHD

RADx Data Program: RADx-UP

Release Date: 12/07/2023

DOI: 10.60773/v97k-6w36

Study Description: Racial/ethnic minority and low socioeconomic status (SES) populations suffer profound health inequities across a wide variety of conditions as well as a disproportionate burden of the negative health consequences of the COVID-19 pandemic. Latinos make up ~14% of the Utah population vs. ~21% of Utah's COVID-19 cases (50% higher) and the case rate is over 3-fold higher in neighborhoods characterized by high vs. low deprivation. In the Utah 2020-2021 school year, there have been 36,484 school-associated cases of COVID-19. The ongoing partnerships with the Utah Department of Health (UDOH) allowed access to real-time information on "hotspot schools" across the state. One of the Utah school district partners, Granite School District (n=85 schools), had the 3rd highest number of cases of COVID-19 and 45% of its schools have a student population with >50% eligible to receive free/reduced lunch and 60% have a student population that is >50% ethnic minority. Schools bear a large part of the burden of managing COVID-19 testing and communicating with parents about testing their children. Few schools in Utah have information technology systems in place to support systematic communication with parents about student COVID-19 testing and tracking testing outcomes. Through the existing RADx-UP grant (UL1TR002538-03S4), the team developed a text messaging and health navigator infrastructure that was deployed in federally-qualified health centers across Utah. The study chose to use text messaging because it is widely available in underserved communities, with 97% of individuals with an annual income <$30,000 and 96% with educational attainment of high school or less having a phone that can text. This project addressed key testing challenges in schools by building on existing collaborations with school districts and with UDOH on COVID-19 testing and existing infrastructure. This study worked closely with schools and the Utah public health system to implement and test a shovel-ready and scalable health information technology approach that delivers automated text messages (TMs) to staff and students' parents around COVID-19 testing. In addition, students in some schools received a health navigator (HN) follow-up to ensure that tests are completed. HN were community members who have been trained in case management. Families were offered the recently FDA-approved in-home serial testing approach if accessing in-person testing was a challenge. Within the context of a cluster-randomized trial, this study employed a rapid cycle design to test interventions on a small scale, using short time frames (<1month) and iterative evaluation cycles. This approach was extremely successful in the current RADx-UP project, SCALE-UP Utah. The proposed trial compared the efficacy of TM versus TM+HN. This project had several potential impacts on COVID-19 testing for elementary and middle school students in disadvantaged school settings: 1] SCALE-UP Counts provided critical data on the impact of pragmatic and scalable approaches to increasing COVID-19 testing and reducing COVID-19-related health inequities among students and their families. 2] The rapid cycle research approach utilized in this project allowed the team to quickly disseminate effective interventions to other schools and adapt interventions to changing testing policies and local outbreaks and rates. 3] The use of HNs who are members of the students' communities maximized the team's ability to integrate communities' cultural factors and strengths and to promote the acceptability of the testing support provided. 4] SCALE-UP Counts hold a significant impact on community transmission of COVID-19 due to the provision of testing to students' immediate household members. Rates of household transmission were 50-75% and thus, ensuring testing for households is essential towards decreasing community spread. 5] The interventions were made readily available for adoption by other disadvantaged school settings and the data will advance population health and implementation science.

Updated Date: 04/17/2024

Principal Investigator: Wu, Yelena

Has Data Files: Yes

Study Domain: At-Home or Over-the-Counter (OTC) Self-Testing; COVID Hotspots; COVID in School Settings; Diagnostic Testing; Social Determinants of Health

Data Collection Method: Antigen Testing Device; Survey

Keywords: COVID Communication via Text Messaging; COVID Hotspot Communities; Families/Legal Guardians of School-aged Children/Young Adults; In-person Testing; School Staff/Stakeholders; School-aged Children/Young Adults

Study Design: Interventional or Clinical Trial

Multi-Center Study: Yes

Study Sites: Granite School District

Data Types: Behavioral; Questionnaire or Survey; Social

Study Start Date: 11/20/2022

Study End Date: 11/20/2023

Species: Human

Estimated Cohort Size: 5600

Study Population Focus: Adults; Children; Hispanics or Latinos; Lower Socioeconomic Status (SES) Populations; Older Adults or Elderly; Racial or Ethnic Minorities; School Communities; Underserved or Vulnerable Populations

ClinicalTrials.gov URL: https://clinicaltrials.gov/study/NCT05112900

Publication URL: https://pubmed.ncbi.nlm.nih.gov/37394503/; https://pubmed.ncbi.nlm.nih.gov/37394508/; https://pubmed.ncbi.nlm.nih.gov/37394512/

Acknowledgement Statement: This study was supported through funding, 3OT2HD108097-01S1, for the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) as part of the RADx-UP program. We are thankful to our collaborators, the Huntsman Cancer Institute and the University of Utah, the Utah Department of Health, and the participating school districts. Additionally, we want to thank the participants that made this study possible. Approved users should acknowledge the provision of data access by dbGaP for accession phs002825.v1.p1, and the NIH RADx Data Hub. Approved users should also acknowledge the specific version(s) of the dataset(s) obtained from the NIH RADx Data Hub.

NIH Grant or Contract Number(s): 3OT2HD108097-01S1

Consent/Data Use Limitations: General Research Use