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Activity Number: 71 - COVID-19 and Survey Research Methods
Type: Contributed
Date/Time: Sunday, August 7, 2022 : 4:00 PM to 5:50 PM
Sponsor: Survey Research Methods Section
Abstract #323067
Title: Modeling State-Level Attitudinal Measures Related to COVID-19 Vaccination of Children Using Survey Data and Administrative Data
Author(s): Nada M Ganesh* and Vicki Pineau and Elizabeth Allen and Zachary H Seeskin and Poulami Maitra and Shalima Zalsha and Kirk Wolter and Tammy Santibanez and James A Singleton and Michael Chen and David Yankey and Yi Mu and Tianyi Zhou and Anurag Jain
Companies: NORC at the University of Chicago and NORC at the University of Chicago and NORC at the University of Chicago and NORC at the University of Chicago and NORC at the University of Chicago and NORC at the University of Chicago and NORC at the University of Chicago and Centers for Disease Control and Prevention and Centers for Disease Control and Prevention and Centers for Disease Control and Prevention and Centers for Disease Control and Prevention and Centers for Disease Control and Prevention and Centers for Disease Control and Prevention and Centers for Disease Control and Prevention
Keywords: COVID-19; composite estimation; National Immunization Survey; small area estimation
Abstract:

The National Immunization Survey-Adult COVID Module (NIS-ACM) and National Immunization Survey-Child COVID Module (NIS-CCM) are random-digit dialing cellular telephone surveys of households, sponsored by the CDC, used to generate weekly and monthly COVID-19 attitudinal measures for adults 18 years and older and children 6 months to 17 years. This paper discusses the use of small area estimation models and methods to generate estimates by state for 5 to 17-year-old children for key attitudinal measures (as reported by the parent or guardian) including vaccination status and intent, COVID-19 vaccine safety, importance of getting vaccinated, and mask wearing in past seven days. Cross-sectional, bivariate, and time-series small area models (i.e., linear mixed models) were used to combine (a) direct survey estimates from the NIS-CCM, (b) direct survey estimates from the NIS-ACM, and (c) regression estimates based on auxiliary data sources.


Authors who are presenting talks have a * after their name.

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