Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Mar 11, 2022
Date Accepted: Jun 7, 2022
Date Submitted to PubMed: Jun 16, 2022
Use of Random Domain Intercept Technology to Track COVID-19 Vaccination Rates in Real-Time Across the United States: Survey Study
ABSTRACT
Background:
Accurate and timely COVID-19 vaccination coverage data is vital to inform targeted, effective messaging and outreach and to identify barriers to equitable health services access.
Objective:
To assess the validity of Random Domain Intercept Technology (RDIT) for tracking self-reported vaccination rates in real-time at the national- and state-level.
Methods:
We employed RDIT, a form of online intercept sampling, from June 30 to July 26, 2021, to reach a broad sample of 63,853 adult (18+ year old) Web users and asked questions related to COVID vaccination.
Results:
At the national level, the RDIT estimate of COVID vaccine coverage was slightly higher than the CDC estimate (69.7% vs. 67.9%). The state-level estimates were strongly, positively correlated, r = .90, p < .001.
Conclusions:
This broad-reaching, real-time data stream, may provide unique advantages for tracking use of a range of vaccines and for timely evaluation of vaccination interventions. Moreover, RDIT could be harnessed to rapidly assess demographic, attitudinal, and behavioral constructs not available in administrative data, which could allow for deeper insights into the real-time predictors of vaccine uptake enabling targeted interventions. Clinical Trial: Johns Hopkins and Emory University’s Institutional Review Boards designated this project as public health practice to inform message development, not human subjects research.
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