Khan, Bilal, Hsuan-Wei Lee, and Kirk Dombrowski. January 2017.
Estimates of population size for hidden and hard-to-reach individuals are of particular interest to health officials when health problems are concentrated in such populations. Efforts to derive these estimates are often frustrated by a range of factors including social stigma or an association with illegal activities that ordinarily preclude conventional survey strategies. This paper builds on and extends prior work that proposed a method to meet these challenges. Here we describe a rigorous formalization of a one-step, network-based population estimation procedure that can be employed under conditions of anonymity. The estimation procedure is designed to be implemented alongside currently accepted strategies for research with hidden populations. Simulation experiments are described that test the efficacy of the method across a range of implementation conditions and hidden population sizes. The results of these experiments show that reliable population estimates can be derived for hidden, networked population as large as 12,500 and perhaps larger for one family of random graphs. As such, the method shows potential for cost-effective implementation health and disease surveillance officials concerned with hidden populations. Limitations and future work are discussed in the concluding section.
Keywords: Capture-recapture, network size estimation, hidden populations, respondent driven sampling, key populations
Prospective Childhood Risk Factors for Gang Involvement among North American Indigenous Adolescents
Hautala, Dane, Kelley Sitter, and Les Whitbeck. 2015. “Prospective Childhood Risk Factors for Gang Involvement among North American Indigenous Adolescents.” Youth Violence and Juvenile Justice. Prepublished May 8, 2015 doi: 10.1177/1541204015585173
Dynamics of the Methamphetamine Markets in New York City
Travis Wendel, Bilal Khan, Kirk Dombrowski, Ric Curtis, Katherine McLean, Evan Misshula, Robert Riggs, David M. Marshall IV
Award Number: 2007-IJ-CX-0110
Using Respondent Driven Sampling, this study piloted an innovative research design mixing qualitative and quantitative data collection methods, and social network analysis, that addresses a gap in information on retail methamphetamine markets and the role of illicit drug markets in consumption. Based on a sample of 132 methamphetamine users, buyers and sellers in New York City (NYC), findings describe a bifurcated market defined by differences in sexual identity, drug use behaviors, social network characteristics, and drug market behaviors. Study findings may be useful to practitioners, policy-makers and researchers in fields including law enforcement, criminal justice, and public health and substance abuse treatment. This project was supported by a grant from National Institute of Justice