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Accepted for/Published in: JMIR Formative Research

Date Submitted: Jan 8, 2024
Date Accepted: Sep 24, 2024

The final, peer-reviewed published version of this preprint can be found here:

Association of Drugs for Sale on the Internet and Official Health Indicators: Darknet Parsing and Correlational Study

Soshnikov S Sr, Bekker S, Idrisov B, Vasiliy V Sr

Association of Drugs for Sale on the Internet and Official Health Indicators: Darknet Parsing and Correlational Study

JMIR Form Res 2024;8:e56006

DOI: 10.2196/56006

PMID: 39546792

PMCID: 11607563

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Closer Look at Illicit Drug Availability and Public Health in Regions: Combining the Darknet Drugs Data and Official Health-Related Indicators.

  • Sergey Soshnikov Sr; 
  • Svetlana Bekker; 
  • Bulat Idrisov; 
  • Vassov Vasiliy Sr

ABSTRACT

Background:

Studying illicit drug circulation and its effects on population health is complicated due to its criminal nature. Illegal drug markets have evolved with technology, moving online to the “darknet.” Previous research has analyzed darknet market listings and customer reviews. Research tools include public health surveys and medical reports but lack neutral data on drugs' spread and impact. This study fills this gap by analyzing the amount of drugs traded on the darknet market.

Objective:

This study's main objective is to bridge Public Health and the investigation of the illegal drug market. By analyzing the scale and nature of drug availability, the frequency of offers, and the regional distribution of illicit drug activities on a Hydra market, we aim to link these findings with official indicators of illegal drug use disorders.

Methods:

We web-parsed the Hydra Darknet narcotics marketplace using the Python code. The data set encompassed 3045 individual sellers marketing 6721 unique products via 58563 distinct postings, each representing specific quantities sold in different Russian regions—data extraction dates: August-December 2019. In the second stage, we collected 31 variables from official sources (Ministry of Health, Police reports, etc.) to make comparisons and to check how these indicators relate to Hydra data about amounts and types of selling drugs in every 85 Russian regions (oblast). The data were obtained from official sources (statistical materials). Maps, diagrams, correlation matrixes, and applied observational statistical methods were used.

Results:

In 2019, Russia's Darknet circulated a minimum of 124 kilograms of narcotics daily in small batches, with a notable decrease during COVID-19. Cannabis significantly dominated the market, being ten times more prevalent than opiates, and cannabis products' higher availability in the region is linked with reduced opiate overdoses. High HIV rates among drug users are linked with the amounts of opiates by region. Regional drug consumption varied, influenced by socioeconomic and cultural factors. For example, while marijuana constituted 20- 30% of total consumption, Krasnodar showed unusually high opiate use (22.50 grams per 100,000). Urban areas reported more drug use than rural, with regional anomalies like Karelia and Chukotka indicating unique local influences.

Conclusions:

This study underscores the importance of a region-specific approach to drug policy in Russia. Policymakers should consider the unique contexts of each region, including the prevalent types of drugs, socioeconomic factors, and local attitudes toward drug use. While nationwide policies can provide a broad framework for combating drug use and related HIV and its associated harms, region-specific strategies are critical for effectively addressing local realities. Clinical Trial: None to declare


 Citation

Please cite as:

Soshnikov S Sr, Bekker S, Idrisov B, Vasiliy V Sr

Association of Drugs for Sale on the Internet and Official Health Indicators: Darknet Parsing and Correlational Study

JMIR Form Res 2024;8:e56006

DOI: 10.2196/56006

PMID: 39546792

PMCID: 11607563

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