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Design and Preliminary Findings of Adherence to the Self-Testing for Our Protection From COVID-19 (STOP COVID-19) Risk-Based Testing Protocol: Prospective Digital Study.
Herbert, Carly; Kheterpal, Vik; Suvarna, Thejas; Broach, John; Marquez, Juan Luis; Gerber, Ben; Schrader, Summer; Nowak, Christopher; Harman, Emma; Heetderks, William; Fahey, Nisha; Orvek, Elizabeth; Lazar, Peter; Ferranto, Julia; Noorishirazi, Kamran; Valpady, Shivakumar; Shi, Qiming; Lin, Honghuang; Marvel, Kathryn; Gibson, Laura; Barton, Bruce; Lemon, Stephenie; Hafer, Nathaniel; McManus, David; Soni, Apurv.
  • Herbert C; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Kheterpal V; CareEvolution, Inc, Ann Arbor, MI, United States.
  • Suvarna T; CareEvolution, Inc, Ann Arbor, MI, United States.
  • Broach J; Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Marquez JL; Washtenaw County Health Department, Washtenaw, MI, United States.
  • Gerber B; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Schrader S; CareEvolution, Inc, Ann Arbor, MI, United States.
  • Nowak C; CareEvolution, Inc, Ann Arbor, MI, United States.
  • Harman E; CareEvolution, Inc, Ann Arbor, MI, United States.
  • Heetderks W; National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Kelly Services, Bethesda, MD, United States.
  • Fahey N; Department of Pediatrics, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Orvek E; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Lazar P; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Ferranto J; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Noorishirazi K; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Valpady S; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Shi Q; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Lin H; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Marvel K; University of Massachusetts Center for Clinical and Translational Science, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Gibson L; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Barton B; Division of Clinical Informatics, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Lemon S; Program in Digital Medicine, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Hafer N; Division of Infectious Disease, Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • McManus D; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States.
  • Soni A; Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, MA, United States.
JMIR Form Res ; 6(6): e38113, 2022 Jun 16.
Article in English | MEDLINE | ID: covidwho-1875306
ABSTRACT

BACKGROUND:

Serial testing for SARS-CoV-2 is recommended to reduce spread of the virus; however, little is known about adherence to recommended testing schedules and reporting practices to health departments.

OBJECTIVE:

The Self-Testing for Our Protection from COVID-19 (STOP COVID-19) study aims to examine adherence to a risk-based COVID-19 testing strategy using rapid antigen tests and reporting of test results to health departments.

METHODS:

STOP COVID-19 is a 12-week digital study, facilitated using a smartphone app for testing assistance and reporting. We are recruiting 20,000 participants throughout the United States. Participants are stratified into high- and low-risk groups based on history of COVID-19 infection and vaccination status. High-risk participants are instructed to perform twice-weekly testing for COVID-19 using rapid antigen tests, while low-risk participants test only in the case of symptoms or exposure to COVID-19. All participants complete COVID-19 surveillance surveys, and rapid antigen results are recorded within the smartphone app. Primary outcomes include participant adherence to a risk-based serial testing protocol and percentage of rapid tests reported to health departments.

RESULTS:

As of February 2022, 3496 participants have enrolled, including 1083 high-risk participants. Out of 13,730 tests completed, participants have reported 13,480 (98.18%, 95% CI 97.9%-98.4%) results to state public health departments with full personal identifying information or anonymously. Among 622 high-risk participants who finished the study period, 35.9% showed high adherence to the study testing protocol. Participants with high adherence reported a higher percentage of test results to the state health department with full identifying information than those in the moderate- or low-adherence groups (high 71.7%, 95% CI 70.3%-73.1%; moderate 68.3%, 95% CI 66.0%-70.5%; low 63.1%, 59.5%-66.6%).

CONCLUSIONS:

Preliminary results from the STOP COVID-19 study provide important insights into rapid antigen test reporting and usage, and can thus inform the use of rapid testing interventions for COVID-19 surveillance.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Language: English Journal: JMIR Form Res Year: 2022 Document Type: Article Affiliation country: 38113

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Language: English Journal: JMIR Form Res Year: 2022 Document Type: Article Affiliation country: 38113