This paper is in the following e-collection/theme issue:

Depression and Mood Disorders; Suicide Prevention (1392) Big Data (245) Infodemiology and Infoveillance (1369) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1565) GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (113) Mental Health Surveillance and Epidemiology (64) Innovative Methods in Public Health and Surveillance (336) Surveillance Systems (466)

Published on in Vol 9, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35253, first published .
Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study

Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study

Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study

Authors of this article:

Alex Wang1 Author Orcid Image ;   Robert McCarron1 Author Orcid Image ;   Daniel Azzam1 Author Orcid Image ;   Annamarie Stehli1 Author Orcid Image ;   Glen Xiong2 Author Orcid Image ;   Jeremy DeMartini2 Author Orcid Image
Article Authors Cited by (15) Tweetations (5) Metrics

Alex Wang   1 , BSc ;   Robert McCarron   1 , DO ;   Daniel Azzam   1 , MD ;   Annamarie Stehli   1 , MPH ;   Glen Xiong   2 , MD ;   Jeremy DeMartini   2 , MD

1 Department of Psychiatry and Human Behavior, University of California, Irvine, Orange, CA, United States

2 Department of Psychiatry & Behavioral Sciences, University of California, Davis, Sacramento, CA, United States

Corresponding Author:

  • Alex Wang, BSc
  • Department of Psychiatry and Human Behavior
  • University of California, Irvine
  • 101 The City Dr S
  • Orange, CA, 92868
  • United States
  • Phone: 1 8584059768
  • Email: wangaj3@uci.edu