Can Big Data Predict the Rise of Novel Drug Abuse?. (October 2018)

• Record Type: Journal Article
• Authors: Perdue, Robert Todd; Hawdon, James; Thames, Kelly M.
• Is Part Of: Journal of drug issues. Volume 48:Number 4(2018)
• Page Start: 508
• Page End: 518
• Publication Date: 2018-10
• Subjects: novel drugs -- opioids -- big data -- Google Trends -- OxyContin -- heroin; Drug abuse -- Periodicals; Drug and Narcotic Control -- Periodicals; Substance-Related Disorders -- Periodicals; Toxicomanie -- Périodiques; 362.29305
• DOI: 10.1177/0022042618772294
• Languages: English
• ISSNs: 0022-0426

Abstract

Existing novel psychoactive drug (NPD) data are woefully inadequate. This gap is especially critical because NPDs are being developed and introduced at alarming rates and pose significant challenges to law enforcement and health care workers. Scholars in numerous fields have used Internet search query analysis to assess and predict health-related outcomes. Here, we explore the utility of these data for predicting NPD and established drug abuse. Google Trends searches for five novel and two established drugs were correlated with data pulled from the Monitoring the Future (MTF). Google Trends data proved highly correlated with data from MTF for all drugs analyzed. Despite limitations, Google Trends appears to be a promising compliment to existing data, providing real time data that may allow us to predict drug abuse trends and respond more quickly.