National HIDTA Assistance Center

High Intensity Drug Trafficking Areas Program

National Emerging Threats Initiative (NETI)

Mission Statement

The National Emerging Threat Initiative (NETI) aims to identify emerging drug threats through evidence-based practices and provide that information to the HIDTA program and others as an enhanced intelligence product.

Vision Statement

To systematically encumber drug addiction and narcotics trafficking with evidence-based data.

Initiative Program Description

NETI is a poly-drug national trends, intelligence, and best practices sharing initiative designated to coordinate HIDTA emerging threat strategies in affected HIDTA areas and the United States. The initiative focuses on systemic approaches to addressing the illegal drug supply, including the diverted use of legal drugs and collateral issues.

Initiative Strategy

NETI supports identifying, coordinating, and implementing a HIDTA strategy for emerging drug-related threats affecting designated HIDTA areas and the United States.

NETI accomplishes this by identifying emerging drug threats and their patterns, addressing each danger through best practices, and promoting cooperation among public safety, public health, regulators, treatment, and prevention entities.

This HIDTA initiative focuses on intelligence sharing and best practices that address emerging drug threats and their associated issues and problems of concern.

Related explicitly to drug abuse, NETI works with public health/public safety, harm reduction, regulators, prevention, treatment, and other entities to develop measures and establish an innovative methodology. When applied to particular data sets, that methodology identifies criminal behavior characteristics involved in the sale and trafficking of illegal narcotics and drug abuse. NETI supports using these attributes to develop analytical reports and assist public health, public safety, harm reduction, regulators, prevention, treatment, and the general public in exploiting the information for both current and predictive data analysis.