Benjamin M Althouse1, Jon-Patrick Allem2, Matthew A Childers3, Mark Dredze4, John W Ayers5. 1. Santa Fe Institute, Santa Fe, New Mexico. 2. Keck School of Medicine, University of Southern California, Los Angeles. 3. School of Public and International Affairs, University of Georgia, Athens, Georgia. 4. Human Language Technology Center of Excellence, Johns Hopkins University Baltimore, Maryland. 5. Graduate School of Public Health, San Diego State University, San Diego, California. Electronic address: ayers.john.w@gmail.com.
Abstract
BACKGROUND: Associations between economic conditions and health are usually derived from cost-intensive surveys that are intermittently collected with nonspecific measures (i.e., self-rated health). PURPOSE: This study identified how precise health concerns changed during the U.S. Great Recession analyzing Google search queries to identify the concern by the query content and their prevalence by the query volume. METHODS: Excess health concerns were estimated during the Great Recession (December 2008 through 2011) by comparing the cumulative difference between observed and expected (based on linear projections from pre-existing trends) query volume for hundreds of individual terms. As performed in 2013, the 100 queries with the greatest excess were ranked and then clustered into themes based on query content. RESULTS: The specific queries with the greatest relative excess were stomach ulcer symptoms and headache symptoms, respectively, 228% (95% CI=35, 363) and 193% (95% CI=60, 275) greater than expected. Queries typically involved symptomology (i.e., gas symptoms) and diagnostics (i.e., heart monitor) naturally coalescing into themes. Among top themes, headache queries were 41% (95% CI=3, 148); hernia 37% (95% CI=16, 142); chest pain 35% (95% CI=6, 313); and arrhythmia 32% (95% CI=3, 149) greater than expected. Pain was common with back, gastric, joint, and tooth foci, with the latter 19% (95% CI=4, 46) higher. Among just the top 100, there were roughly 205 million excess health concern queries during the Great Recession. CONCLUSIONS: Google queries indicate that the Great Recession coincided with substantial increases in health concerns, hinting at how population health specifically changed during that time.
BACKGROUND: Associations between economic conditions and health are usually derived from cost-intensive surveys that are intermittently collected with nonspecific measures (i.e., self-rated health). PURPOSE: This study identified how precise health concerns changed during the U.S. Great Recession analyzing Google search queries to identify the concern by the query content and their prevalence by the query volume. METHODS: Excess health concerns were estimated during the Great Recession (December 2008 through 2011) by comparing the cumulative difference between observed and expected (based on linear projections from pre-existing trends) query volume for hundreds of individual terms. As performed in 2013, the 100 queries with the greatest excess were ranked and then clustered into themes based on query content. RESULTS: The specific queries with the greatest relative excess were stomach ulcer symptoms and headache symptoms, respectively, 228% (95% CI=35, 363) and 193% (95% CI=60, 275) greater than expected. Queries typically involved symptomology (i.e., gas symptoms) and diagnostics (i.e., heart monitor) naturally coalescing into themes. Among top themes, headache queries were 41% (95% CI=3, 148); hernia 37% (95% CI=16, 142); chest pain 35% (95% CI=6, 313); and arrhythmia 32% (95% CI=3, 149) greater than expected. Pain was common with back, gastric, joint, and tooth foci, with the latter 19% (95% CI=4, 46) higher. Among just the top 100, there were roughly 205 million excess health concern queries during the Great Recession. CONCLUSIONS: Google queries indicate that the Great Recession coincided with substantial increases in health concerns, hinting at how population health specifically changed during that time.
Authors: John W Ayers; Benjamin M Althouse; Jon-Patrick Allem; Eric C Leas; Mark Dredze; Rebecca S Williams Journal: Am J Prev Med Date: 2016-02-11 Impact factor: 5.043
Authors: Jon-Patrick Allem; Patricia Escobedo; Kar-Hai Chu; Daniel W Soto; Tess Boley Cruz; Jennifer B Unger Journal: Tob Control Date: 2016-03-08 Impact factor: 7.552
Authors: Eric C Leas; Benjamin M Althouse; Mark Dredze; Nick Obradovich; James H Fowler; Seth M Noar; Jon-Patrick Allem; John W Ayers Journal: PLoS One Date: 2016-08-02 Impact factor: 3.240
Authors: Alison Callahan; Igor Pernek; Gregor Stiglic; Jure Leskovec; Howard R Strasberg; Nigam Haresh Shah Journal: J Med Internet Res Date: 2015-08-20 Impact factor: 5.428
Authors: Nicola Luigi Bragazzi; Guglielmo Dini; Alessandra Toletone; Francesco Brigo; Paolo Durando Journal: PLoS One Date: 2016-11-02 Impact factor: 3.240
Authors: Benjamin M Althouse; Samuel V Scarpino; Lauren Ancel Meyers; John W Ayers; Marisa Bargsten; Joan Baumbach; John S Brownstein; Lauren Castro; Hannah Clapham; Derek At Cummings; Sara Del Valle; Stephen Eubank; Geoffrey Fairchild; Lyn Finelli; Nicholas Generous; Dylan George; David R Harper; Laurent Hébert-Dufresne; Michael A Johansson; Kevin Konty; Marc Lipsitch; Gabriel Milinovich; Joseph D Miller; Elaine O Nsoesie; Donald R Olson; Michael Paul; Philip M Polgreen; Reid Priedhorsky; Jonathan M Read; Isabel Rodríguez-Barraquer; Derek J Smith; Christian Stefansen; David L Swerdlow; Deborah Thompson; Alessandro Vespignani; Amy Wesolowski Journal: EPJ Data Sci Date: 2015-10-16 Impact factor: 3.184
Authors: John W Ayers; J Lee Westmaas; Eric C Leas; Adrian Benton; Yunqi Chen; Mark Dredze; Benjamin M Althouse Journal: JMIR Public Health Surveill Date: 2016-03-31
Authors: Oliver Gruebner; Sarah R Lowe; Martin Sykora; Ketan Shankardass; S V Subramanian; Sandro Galea Journal: PLoS One Date: 2017-07-19 Impact factor: 3.240