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Activity Number: 87
Type: Contributed
Date/Time: Sunday, August 4, 2013 : 4:00 PM to 5:50 PM
Sponsor: Survey Research Methods Section
Abstract - #309261
Title: Estimation Methodology for Weekly Surveys of Influenza Vaccination Rates
Author(s): Kennon Copeland*+ and Nicholas Davis and Lin Liu and Nadarajasundaram Ganesh and James A. Singleton and Tammy Santibanez
Companies: NORC and NORC at the University of Chicago and NORC at the University of Chicago and NORC at the University of Chicago and NCIRD, Centers for Disease Control and Prevention and NCIRD, Centers for Disease Control and Prevention
Keywords: Composite Estimation ; National Immunization Survey ; Trend Estimates ; Survival Analysis
Abstract:

Rapid-response surveillance of influenza vaccination rates involves collection of weekly survey data, typically based on relatively small sample sizes yielding relatively high variability. Such variability also adversely affects the stability of estimates across time, the result being estimated trends that may show occasional declines, even though the true population trends are by definition non-decreasing. Composite estimation, combining data across time periods, offers the opportunity for more stable estimates of coverage levels and trends as well as estimated trends less subject to period-to-period decreases. Use of survival analysis techniques is another alternative that ensures non-decreasing estimated trends. This presentation will profile variability associated with direct estimates of levels and trends associated with the influenza module of the National Immunization Survey, propose a composite estimation and a survival analysis approach for combining data across time, assess the variability associated with composite and survival estimates of weekly influenza vaccination rates, and discuss potential error associated with use of data collected in different survey periods.


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