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Cluster analysis of adults unvaccinated for COVID-19 based on behavioral and social factors, National Immunization Survey-Adult COVID Module, United States.
Meng, Lu; Masters, Nina B; Lu, Peng-Jun; Singleton, James A; Kriss, Jennifer L; Zhou, Tianyi; Weiss, Debora; Black, Carla L.
  • Meng L; CDC COVID-19 Response Team; General Dynamics Information Technology Inc., Falls Church, VA, United States of America. Electronic address: PRJ8@cdc.gov.
  • Masters NB; CDC COVID-19 Response Team; Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, CDC; Epidemic Intelligence Service, CDC, Atlanta, GA, United States of America.
  • Lu PJ; CDC COVID-19 Response Team; Immunization Services Division, National Center for Immunization and Respiratory Diseases, CDC, Atlanta, GA, United States of America.
  • Singleton JA; CDC COVID-19 Response Team; Immunization Services Division, National Center for Immunization and Respiratory Diseases, CDC, Atlanta, GA, United States of America.
  • Kriss JL; CDC COVID-19 Response Team; Immunization Services Division, National Center for Immunization and Respiratory Diseases, CDC, Atlanta, GA, United States of America.
  • Zhou T; Immunization Services Division, National Center for Immunization and Respiratory Diseases, CDC, Atlanta, GA, United States of America; Leidos Inc., Atlanta, GA, United States of America.
  • Weiss D; CDC COVID-19 Response Team; Division of State and Local Readiness, Center for Preparedness and Response, CDC.
  • Black CL; CDC COVID-19 Response Team; Immunization Services Division, National Center for Immunization and Respiratory Diseases, CDC, Atlanta, GA, United States of America.
Prev Med ; 167: 107415, 2023 02.
Article in English | MEDLINE | ID: covidwho-2165969
ABSTRACT
By the end of 2021, approximately 15% of U.S. adults remained unvaccinated against COVID-19, and vaccination initiation rates had stagnated. We used unsupervised machine learning (K-means clustering) to identify clusters of unvaccinated respondents based on Behavioral and Social Drivers (BeSD) of COVID-19 vaccination and compared these clusters to vaccinated participants to better understand social/behavioral factors of non-vaccination. The National Immunization Survey Adult COVID Module collects data on U.S. adults from September 26-December 31,2021 (n = 187,756). Among all participants, 51.6% were male, with a mean age of 61 years, and the majority were non-Hispanic White (62.2%), followed by Hispanic (17.2%), Black (11.9%), and others (8.7%). K-means clustering procedure was used to classify unvaccinated participants into three clusters based on 9 survey BeSD items, including items assessing COVID-19 risk perception, social norms, vaccine confidence, and practical issues. Among unvaccinated adults (N = 23,397), 3 clusters were identified the "Reachable" (23%), "Less reachable" (27%), and the "Least reachable" (50%). The least reachable cluster reported the lowest concern about COVID-19, mask-wearing behavior, perceived vaccine confidence, and were more likely to be male, non-Hispanic White, with no health conditions, from rural counties, have previously had COVID-19, and have not received a COVID-19 vaccine recommendation from a healthcare provider. This study identified, described, and compared the characteristics of the three unvaccinated subgroups. Public health practitioners, healthcare providers and community leaders can use these characteristics to better tailor messaging for each sub-population. Our findings may also help inform decisionmakers exploring possible policy interventions.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Vaccines / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Adult / Female / Humans / Male / Middle aged Language: English Journal: Prev Med Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Vaccines / COVID-19 Type of study: Observational study / Prognostic study Topics: Vaccines Limits: Adult / Female / Humans / Male / Middle aged Language: English Journal: Prev Med Year: 2023 Document Type: Article