Estimating the Size of the Methamphetamine-Using Population in New York City Using Network Sampling Techniques

Area of Science:

• Epidemiology
• Network Analysis
• Public Health

Background:

• Understanding the dynamics of illicit drug markets is crucial for public health interventions.
• Estimating the size of hidden populations, such as illicit drug users, presents significant methodological challenges.
• Previous studies often struggle with respondent anonymity and accurate population size estimation.

Purpose of the Study:

• To estimate the size of the networked population involved in methamphetamine use in New York City.
• To describe and validate novel network sampling and capture-recapture techniques for hidden populations.
• To assess the feasibility of maintaining respondent and network alter anonymity during data collection.

Main Methods:

• Network sampling was employed, initiating with a seed sample and expanding by requesting co-use contacts.
• Capture-recapture estimation was performed using links identified through demographic and anonymized telephone number matching ('telefunken').
• Procedures for estimating false matches and developing confidence intervals for population estimates were detailed.

Main Results:

• A total population estimate of 12,229 individuals was derived.
• The estimated population size had a confidence interval ranging from 8,235 to 23,750.
• The methodology successfully maintained anonymity for both respondents and their network contacts.

Conclusions:

• Network sampling combined with capture-recapture offers a viable approach for estimating hidden populations while preserving anonymity.
• The described techniques provide a robust method for understanding the scale of illicit drug use networks.
• Larger sample sizes than the 132 participants interviewed may be necessary to achieve higher confidence levels in population estimates.