People who inject drugs in metropolitan Chicago: A meta-analysis of data from 1997-2017 to inform interventions and computational modeling toward hepatitis C microelimination

Boodram, Basmattee; Mackesy-Amiti, Mary Ellen; Khanna, Aditya; Brickman, Bryan; Dahari, Harel; Ozik, Jonathan

doi:10.1371/journal.pone.0248850

Title: People who inject drugs in metropolitan Chicago: A meta-analysis of data from 1997-2017 to inform interventions and computational modeling toward hepatitis C microelimination

Journal Article · 12 January 2022 · PLoS ONE

DOI: https://doi.org/10.1371/journal.pone.0248850 · OSTI ID:1958016

Boodram, Basmattee ^[1];

^[1];

^[2];

^[3]; Dahari, Harel ^[4];

^[5]

Univ. of Illinois, Chicago, IL (United States)
Brown Univ., Providence, RI (United States)
Univ. of Chicago, IL (United States)
Loyola University Medical Center, Maywood, IL (United States)
Argonne National Lab. (ANL), Lemont, IL (United States)

Progress toward hepatitis C virus (HCV) elimination in the United States is not on track to meet targets set by the World Health Organization, as the opioid crisis continues to drive both injection drug use and increasing HCV incidence. A pragmatic approach to achieving this is using a microelimination approach of focusing on high-risk populations such as people who inject drugs (PWID). Computational models are useful in understanding the complex interplay of individual, social, and structural level factors that might alter HCV incidence, prevalence, transmission, and treatment uptake to achieve HCV microelimination. However, these models need to be informed with realistic sociodemographic, risk behavior and network estimates on PWID. We conducted a meta-analysis of research studies spanning 20 years of research and interventions with PWID in metropolitan Chicago to produce parameters for a synthetic population for realistic computational models (e.g., agent-based models). We then fit an exponential random graph model (ERGM) using the network estimates from the meta-analysis in order to develop the network component of the synthetic population.

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Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE; National Institutes of Health (NIH)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1958016

Journal Information:: PLoS ONE, Journal Name: PLoS ONE Journal Issue: 1 Vol. 17; ISSN 1932-6203

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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