Population smoking trends are principally documented by aggregating individual responses to health surveys that are only collected intermittently. As a result, most evaluations of population tobacco control may be confounded when multiple measures take effect in the same year. Real-time smoking trends would allow investigators to temporally associate population smoking with specific tobacco control measures, thereby potentially better cataloging the effectiveness of specific tobacco control measures. Until now there has not been an adequate data source for real-time population smoking surveillance. The Internet is the most utilized health resource on the globe, and some pioneering work in infectious disease epidemiology shows aggregate Internet search queries may be used to validly estimate population heath trends. We hypothesize changes in smoking-related Internet search queries may capture population smoking trends, with fine temporal resolution to inform tobacco control evaluations. To demonstrate their utility, these trends will b used to evaluate the effectiveness of the Great American Smokeout and New York's (NY) 2010 cigarette excise tax increase, hypothesizing these measures will reduce smoking. Real-time smoking trends will be disseminated through a public web application, Tobacco Trends (www.tobaccotrends.org), with smoking trends for 2004 onward to give investigators, sponsors, and policy makers the ability to rapidly evaluate tobacco control measures based on population smoking trends.

Public Health Relevance

This application addresses the lack of real-time population smoking surveillance to support the evidence-base for tobacco control. This application uses a unique resource-Internet search queries and develops methods to monitor population-smoking trends in real-time, leveraging these trends for tobacco control evaluations, and making these trends available online to the community of clinicians, scientists and policy makers for their own analyses.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Exploratory/Developmental Grants (R21)
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Special Emphasis Panel (ZRG1-SSPS-H (09))
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Kaufman, Annette R
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San Diego State University
Public Health & Prev Medicine
Other Domestic Higher Education
San Diego
United States
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Leas, Eric C; Ayers, John W; Strong, David R et al. (2017) Which cigarettes do Americans think are safer? A population-based analysis with wave 1 of the PATH study. Tob Control 26:e59-e60
Ayers, John W; Westmaas, J Lee; Leas, Eric C et al. (2016) Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout. JMIR Public Health Surveill 2:e16
Ayers, John W; Althouse, Benjamin M; Allem, Jon-Patrick et al. (2016) Revisiting the Rise of Electronic Nicotine Delivery Systems Using Search Query Surveillance. Am J Prev Med 50:e173-e181
Ayers, John W; Althouse, Benjamin M; Emery, Sherry (2015) Changes in Internet searches associated with the ""Tips from Former Smokers"" campaign. Am J Prev Med 48:e27-9
Ayers, John W; Althouse, Benjamin M (2015) ""Tips From Former Smokers"" Can Benefit From Considering All Available Data: Reply to McAfee et al. Am J Prev Med 49:e133-4
Ayers, John W; Althouse, Benjamin M; Johnson, Morgan et al. (2014) Circaseptan (weekly) rhythms in smoking cessation considerations. JAMA Intern Med 174:146-8
Ayers, John W; Althouse, Benjamin M; Dredze, Mark (2014) Could behavioral medicine lead the web data revolution? JAMA 311:1399-400