• Southern medical journal · Dec 2021

    Lower Intent to Comply with COVID-19 Public Health Recommendations Correlates to Higher Disease Burden in Following 30 Days.

    • Robert P Lennon, Aleksandra E Zgierska, Erin L Miller, Bethany Snyder, Aparna Keshaviah, Xindi C Hu, Hanzhi Zhou, and Lauren Jodi Van Scoy.
    • From the Departments of Family and Community Medicine, Internal Medicine, and the Qualitative and Mixed Methods Core, Pennsylvania State University College of Medicine, Hershey, and Mathematica. Princeton, New Jersey.
    • South. Med. J. 2021 Dec 1; 114 (12): 744750744-750.

    ObjectivesWe sought to determine whether self-reported intent to comply with public health recommendations correlates with future coronavirus disease 2019 (COVID-19) disease burden.MethodsA cross-sectional, online survey of US adults, recruited by snowball sampling, from April 9 to July 12, 2020. Primary measurements were participant survey responses about their intent to comply with public health recommendations. Each participant's intent to comply was compared with his or her local COVID-19 case trajectory, measured as the 7-day rolling median percentage change in COVID-19 confirmed cases within participants' 3-digit ZIP code area, using public county-level data, 30 days after participants completed the survey.ResultsAfter applying raking techniques, the 10,650-participant sample was representative of US adults with respect to age, sex, race, and ethnicity. Intent to comply varied significantly by state and sex. Lower reported intent to comply was associated with higher COVID-19 case increases during the following 30 days. For every 3% increase in intent to comply with public health recommendations, which could be achieved by improving average compliance by a single point for a single item, we estimate a 9% reduction in new COVID-19 cases during the subsequent 30 days.ConclusionsSelf-reported intent to comply with public health recommendations may be used to predict COVID-19 disease burden. Measuring compliance intention offers an inexpensive, readily available method of predicting disease burden that can also identify populations most in need of public health education aimed at behavior change.

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