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Activity Number: 672
Type: Topic Contributed
Date/Time: Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
Sponsor: Social Statistics Section
Abstract - #308813
Title: Opinion Dynamics Modeling in Tobacco Control Policy
Author(s): Patrick D. Finley*+ and Thomas W. Moore and Gregory J. Lambert and Ryan Hammer and Taylor E. Berger and Nancy S. Brodsky and Ben Apelberg and Bridget Ambrose and Danny Lee and Antonio Paredes and George Rochester and Robert J. Glass
Companies: Sandia National Laboratories and Sandia National Laboratories and Sandia National Laboratories and Sandia National Laboratories and Sandia National Laboratories and Sandia National Laboratories and Center for Tobacco Products and Center for Tobacco Products/FDA and Center for Tobacco Products/FDA and US-Food and Drug Administration and Center for Tobacco Products/FDA and Sandia National Laboratories
Keywords: Tobacco ; Public Health ; Agent-Based Model ; Social Network ; Advertising ; Smoking

Modeling effects of social and media influences on tobacco use provides information vital for tobacco regulation policy decisions. Opinion Dynamics (OD) models simulate the flow of information through social networks and resultant behavior changes. We model the effects of advertising campaigns, interpersonal communication and public health messaging on individual decisions to start or quit tobacco use as modulated by addiction. The topology of dynamic social networks and the content, sequencing and targeting of media messages can dramatically affect patterns of tobacco-use initiation and cessation. Individual risk tolerance and perceived risk associated with specific product types generate patterns of tobacco uptake consistent with real world data. We apply logistic regression and latent factor analysis to demographic, psychometric and survey data to help parameterize and calibrate the model. Sensitivity analysis using variance decomposition methods applied to Gaussian process surrogates help prioritize potential directions for regulatory action. Uncertainty propagation provides guidance on robustness of alternative regulatory policies to stochastic and demographic variation.

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