a University of Texas study reveals Illegal drug sales on the dark web are common, hard to detect and are fueling America's addiction epidemic.
Opioids include prescription painkillers (such as oxycodone) and illegal drugs (such as heroin and fentanyl).
"People are struggling from the effects of addiction," said Tiffany Champagne-Langabeer, senior author of a new investigation of illegal drug sales. "This study shines a light on the sophisticated methods of how the supply of opioids is coming into this country."
Accidental opioid overdoses cause more deaths in the United States than traffic accidents and suicides, she noted in a university news release.
Champagne-Langabeer is an assistant professor of health informatics at the University of Texas Health Science Center at Houston.
Using a programming language to probe the dark web, the researchers found more than 248,000 opioid-related listings on 10 anonymous online marketplaces.
That included just over 28,100 opioid product listings and over 13,500 opioid promotional and review forum traces. These were linked to over 5,100 opioid suppliers' IDs and nearly 2,800 buyers' IDs.
Postings included product photos and reviews, as well as instructions for buying the items. Soon after a product had been posted and sold, the seller and site disappeared, according to the report recently published in the Journal of Medical Internet Research.
Champagne-Langabeer said there is a surprising level of sophistication to this trade.
"In order to buy the product, you have to use cryptocurrency, which requires a high level of technology," she said. "When you think of opioids or heroin, you think of drugs being sold on the street, but I think what we found here is that it is a lot more complex and sophisticated in how they are able to obtain and distribute these products. People can buy and sell at a much faster rate globally using the web."
The researchers hope their findings will prompt policymakers to take steps to curb dark web sales of opioids.
"This is just the first of many studies to come that can potentially stop the large trade of opioids," Champagne-Langabeer said. "I think we proved that by using coding language, we are able to match their level of sophistication and hopefully one day control the source."
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