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Activity Number: 341 - Statistical Applications in Infectious Disease Epidemiology
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #324722
Title: Segmented regression modeling of tuberculosis incidence surveillance data in the U.S. to analyze potentially changing trends
Author(s): Brock Stewart* and Lori Armstrong and Carla Winston
Companies: Centers for Disease Control and Prevention and Centers for Disease Control and Prevention and Centers for Disease Control and Prevention
Keywords: Tuberculosis ; Segmented regression ; epidemiology surveillance
Abstract:

For many years the annual incidence of Mycobacterium tuberculosis (TB) in the U.S. declined. From 1993 to 2012 the incidence of TB declined 67 percent, from 9.7 to 3.2 cases per 100,000. With the release of the 2015 National TB Surveillance System data, it was discovered that TB incidence in the U.S. had apparently leveled from years 2013--2015. In this presentation we will describe the methods we used to better understand the current leveling incidence trend. We performed a detailed and comprehensive analysis of rates and case count trends, accounting for demographic subgroups and jurisdictions, and of trends in clinical and risk factor characteristics. We used log-linear segmented regression models as part of our analysis to detect statistically significant differences between observed changes in case counts in years 2013-2015 versus what the fitted model predicts for that year range. We discuss differences found in changing trends between various factors, such as country of origin, and racial/ethnic groups.


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

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