Observational study into prescription medicines offered for sale on the dark web
Abstract
Abstract:
Background: The phenomenon of counterfeit drugs was widely discussed during the last decades.
According to the World Health Organisation (WHO), counterfeit drugs are those that are
knowingly mislabelled, and they may contain little or no active ingredient. Indeed, investigators
have found toxic and fatal ingredients in some counterfeit drugs. The sale of these products is
facilitated by the crypto market, and the products most traded are illicit opiates, stimulants, and
prescription drugs. Consumers beside US dollars they use Bitcoin, a digital currency, to buy the
products. Silk Road is a popular marketplace that was first discovered in 2011. Users access Silk
Road using specialized TOR software.
Objectives: The aim of this observational study is to find the relationship between the prices and
weight in grams and strength of tablets in milligrams of the traded counterfeit/falsified prescription
drugs in the Silk Road marketplace during a specific period.
Method and setting: The setting of the study was conducted in the dark web at the SilkRoad
platform, to open the dark web the steps initially included downloading TOR software, this link
was obtained from google. The second step was to create an anonymous account to login into the
platform. Data collection was based on drug advertisements data gathered from the website in the
period from the 9th of June 2021 until the 24th of June 2021 were analysed by SSP software.
Results: 168 advertisements were analysed in the study. Analysis of 39 cocaine advertisements
results were 95% CI (9.95– 48.71) and p value< 0.001; heroine analysis includes 44 advertisements
resulted in 95%CI (12.1 – 44.21) and p value< 0.001, both models were significant. While the
other models their results were not significant and have some limitations.
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Conclusion: The final finding and results of the study indicate that there are a strong models to be
studied and create good results and there are weak models that need further investigations.