TY - JOUR
T1 - Analyzing client behavior in a syringe exchange program
AU - Yang, Haoxiang
AU - Hu, Yue
AU - Morton, David P.
N1 - Publisher Copyright:
Copyright © 2018, The Authors. All rights reserved.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2018/12/4
Y1 - 2018/12/4
N2 - Multiple syringe exchange programs serve the Chicago metropolitan area, providing support for drug users to help prevent infectious diseases. Using data from one program over a ten-year period, we study the behavior of its clients, focusing on the temporal process governing their visits to service locations and on their demographics. We construct a phase-type distribution with an affine relationship between model parameters and features of an individual client. The phase-type distribution governs inter-arrival times between reoccurring visits of each client and is informed by characteristics of a client including age, gender, ethnicity, and more. The inter-arrival time model is a sub-model in a simulation that we construct for the larger system, which allows us to provide a personalized prediction regarding the client’s time-to-return to a service location so that better intervention decisions can be made with the help of simulation.
AB - Multiple syringe exchange programs serve the Chicago metropolitan area, providing support for drug users to help prevent infectious diseases. Using data from one program over a ten-year period, we study the behavior of its clients, focusing on the temporal process governing their visits to service locations and on their demographics. We construct a phase-type distribution with an affine relationship between model parameters and features of an individual client. The phase-type distribution governs inter-arrival times between reoccurring visits of each client and is informed by characteristics of a client including age, gender, ethnicity, and more. The inter-arrival time model is a sub-model in a simulation that we construct for the larger system, which allows us to provide a personalized prediction regarding the client’s time-to-return to a service location so that better intervention decisions can be made with the help of simulation.
KW - Discrete-event simulation
KW - Personalized prediction
KW - Phase-type distribution
KW - Syringe exchange program
UR - http://www.scopus.com/inward/record.url?scp=85095206839&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85095206839&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:85095206839
JO - Free Radical Biology and Medicine
JF - Free Radical Biology and Medicine
SN - 0891-5849
ER -