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Title: Agent-based model forecasts aging of the population of people who inject drugs in metropolitan Chicago and changing prevalence of hepatitis C infections

Journal Article · · PLoS ONE
 [1];  [2];  [3];  [4];  [5];  [6];  [7]
  1. Univ. of Illinois at Chicago, Chicago, IL (United States); Loyola Univ. Medical Center, Maywood, IL (United States); Food and Drug Administration, Silver Springs, MD (United States)
  2. Univ. of Illinois at Chicago, Chicago, IL (United States)
  3. Chicago Dept. of Public Health, Chicago, IL (United States)
  4. George Mason Univ., Fairfax, VA (United States)
  5. Loyola Univ. Medical Center, Maywood, IL (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  6. Food and Drug Administration, Silver Springs, MD (United States)
  7. Univ. Medicine Greifswald (Germany)

People who inject drugs (PWID) are at high risk for blood-borne pathogens transmitted during the sharing of contaminated injection equipment, particularly hepatitis C virus (HCV). HCV prevalence is influenced by a complex interplay of drug-use behaviors, social networks, and geography, as well as the availability of interventions, such as needle exchange programs. To adequately address this complexity in HCV epidemic forecasting, we have developed a computational model, the Agent-based Pathogen Kinetics model (APK). APK simulates the PWID population in metropolitan Chicago, including the social interactions that result in HCV infection. We used multiple empirical data sources on Chicago PWID to build a spatial distribution of an in silico PWID population and modeled networks among the PWID by considering the geography of the city and its suburbs. APK was validated against 2012 empirical data (the latest available) and shown to agree with network and epidemiological surveys to within 1%. For the period 2010–2020, APK forecasts a decline in HCV prevalence of 0.8% per year from 44(±2)% to 36(±5)%, although some sub-populations would continue to have relatively high prevalence, including Non-Hispanic Blacks, 48(±5)%. The rate of decline will be lowest in Non-Hispanic Whites and we find, in a reversal of historical trends, that incidence among non-Hispanic Whites would exceed incidence among Non-Hispanic Blacks (0.66 per 100 per years vs 0.17 per 100 person years). APK also forecasts an increase in PWID mean age from 35(±1) to 40(±2) with a corresponding increase from 59(±2)% to 80(±6)% in the proportion of the population >30 years old. As a result, our studies highlight the importance of analyzing subpopulations in disease predictions, the utility of computer simulation for analyzing demographic and health trends among PWID and serve as a tool for guiding intervention and prevention strategies in Chicago, and other major cities.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1223795
Alternate ID(s):
OSTI ID: 1235895
Report Number(s):
LA-UR-15-20358
Journal Information:
PLoS ONE, Vol. 10, Issue 9; ISSN 1932-6203
Publisher:
Public Library of ScienceCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 17 works
Citation information provided by
Web of Science

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Cited By (6)

High-Risk Geographic Mobility Patterns among Young Urban and Suburban Persons who Inject Drugs and their Injection Network Members journal September 2017
Combination interventions for Hepatitis C and Cirrhosis reduction among people who inject drugs: An agent-based, networked population simulation experiment journal November 2018
Combination interventions for Hepatitis C and Cirrhosis reduction among people who inject drugs: An agent-based, networked population simulation experiment text January 2018
Combination interventions for Hepatitis C and Cirrhosis reduction among people who inject drugs: An agent-based, networked population simulation experiment text January 2017
Sensitivity analysis of Repast computational ecology models with R/Repast journal November 2016
Analyzing Repast Symphony models in R with RRepast package journal May 2016