An analysis of morbidity and mortality using Google Trends

Journal of Human Behavior in the Social Environment

Volumn 27, Issue 6, 2017, Pages 559-570

  Ricketts, Comfort F ^a   Silva, Carlos G ^a  

^a NEW MEXICO STATE UNIVERSITY   (United States)

Author keywords

Google Trends; internet search; morbidity; mortality; technology

Indexed keywords

EID: 85016099963     PISSN: 10911359     EISSN: 15403556     Source Type: Journal    
DOI: 10.1080/10911359.2017.1299658     Document Type: Article

References (23)

1. Ayers, J. W., Althouse, B. M., Allem, J. P., Rosenquist, J. N., & Ford, D. E., (2013). Seasonality in seeking mental health information on Google. American Journal of Preventive Medicine, 44(5), 520–525. doi:10.1016/j.amepre.2013.01.012
2. Bauer, U. E., Briss, P. A., Goodman, R. A., & Bowman, B. A., (2014). Prevention of chronic disease in the 21st century:Elimination of the leading preventable causes of premature death and disability in the USA. The Lancet, 384(9937), 45–52. doi:10.1016/S0140-6736(14)60648-6
3. Carneiro, H. A., & Mylonakis, E., (2009). Google trends:A web-based tool for real-time surveillance of disease outbreaks. Clinical Infectious Diseases, 49(10), 1557–1564. doi:10.1086/599193
4. Cavazos-Rehg, P. A., Krauss, M. J., Spitznagel, E. L., Lowery, A., Grucza, R. A., Chaloupka, F. J., & Bierut, L. J., (2015). Monitoring of non-cigarette tobacco use using Google Trends. Tobacco Control, 24, 249–255.
5. Centers for Disease Control and Prevention (CDC). (2014, December 21). Leading causes of death by age group. Retrieved from http://www.cdc.gov/injury/wisqars/pdf/leading_causes_of_death_by_age_group_11-a.pdf.
6. Choi, H., & Varian, H., (2009). Predicting initial claims for unemployment benefits. Retrieved from https://static.googleusercontent.com/media/research.google.com/en//archive/papers/initialclaimsUS.pdf
7. Choi, H., & Varian, H., (2012). Predicting the present with Google Trends. Economic Record, 88(Supp. 1), 2–9.
8. Edelman, B., (2012). Earnings and ratings at Google Answers. Economic Inquiry, 50(2), 309–320.
9. Eysenbach, G., (2006). Infodemiology:Tracking flu-related searches on the web for syndromic surveillance. In AMIA Annual Symposium Proceedings (Vol. 2006, p. 244). Bethesda, MD:American Medical Informatics Association.
10. Frijters, P., Johnston, D. W., Lordan, G., & Shields, M. A., (2013). Exploring the relationship between macroeconomic conditions and problem drinking as captured by Google searches in the US. Social Science & Medicine, 84, 61–68. doi:10.1016/j.socscimed.2013.01.028
11. Hulth, A., & Rydevik, G., (2011). Web query-based surveillance in Sweden during the influenza A (H1N1) 2009 pandemic, April 2009 to February 2010. Euro Surveillance, 16, 18.
12. Kang, M., Zhong, H., He, J., Rutherford, S., & Yang, F., (2013). Using google trends for influenza surveillance in South China. Plos One, 8(1), e55205. doi:10.1371/journal.pone.0055205
13. McCarthy, M. J., (2010). Internet monitoring of suicide risk in the population. Journal of Affective Disorders, 122(3), 277–279. doi:10.1016/j.jad.2009.08.015
14. Milinovich, G. J., Magalhães, R. J. S., & Hu, W., (2015). Role of big data in the early detection of Ebola and other emerging infectious diseases. Lancet Global Health, 3(1), e20–e21. doi:10.1016/S2214-109X(14)70356-0
15. National Cancer Institute (NCI). Cancer statistics animator. Washington, DC:U.S. Mortality Files, National Center for Health Statistics, Centers for Disease Control and Prevention. Retrieved from https://seer.cancer.gov/canstat/
16. Pelat, C., Turbelin, C., Bar-Hen, A., Flahault, A., & Valleron, A. J., (2009). More diseases tracked by using Google Trends. Emerging Infectious Diseases, 15(8), 1327–1328. doi:10.3201/eid1508.090299
17. Sarigul, S., & Rui, H., (2014, June). Nowcasting obesity in the US using Google search volume data. In 2014 AAEA/EAAE/CAES Joint Symposium:Social Networks, Social Media and the Economics of Food, May 29-30, 2014, Montreal, Canada (No. 166113). Agricultural and Applied Economics Association & Canadian Agricultural Economics Society & European Association of Agricultural Economists.
18. Song, T. M., Song, J., An, J. Y., Hayman, L. L., & Woo, J. M., (2014). Psychological and social factors affecting Internet searches on suicide in Korea:A big data analysis of Google search trends. Yonsei Medical Journal, 55(1), 254–263. doi:10.3349/ymj.2014.55.1.254
19. Surveillance, Epidemiology and End Result Program (SEER). (2014, December 21). Cancer statistics animator. Retrieved from http://seer.cancer.gov/canstat/animator/#y=2004f;o=0011633;v1=360000.3FF0000.20.42.
20. Tefft, N., (2011). Insights on unemployment, unemployment insurance, and mental health. Journal of Health Economics, 30(2), 258–264. doi:10.1016/j.jhealeco.2011.01.006
21. Vosen, S., & Schmidt, T., (2011). Forecasting private consumption:Survey‐based indicators vs. Google trends. Journal of Forecasting, 30(6), 565–578.
22. Wu, L., & Brynjolfsson, E., (2014). The future of prediction:How Google searches foreshadow housing prices and sales. In A., Goldfarb, S. M., Greeinstein, and C. E., Tucker (Eds.), Economic analysis of the digital economy (pp. 89–118). Chicago, IL:University of Chicago Press.
23. Yang, A. C., Tsai, S. J., Huang, N. E., & Peng, C. K., (2011). Association of Internet search trends with suicide death in Taipei City, Taiwan, 2004–2009. Journal of Affective Disorders, 132(1), 179–184. doi:10.1016/j.jad.2011.01.019