Literature DB >> 26775738

Modeling a dynamic bi-layer contact network of injection drug users and the spread of blood-borne infections.

Rui Fu1, Alexander Gutfraind2, Margaret L Brandeau3.   

Abstract

Injection drug users (IDUs) are at high risk of acquiring and spreading various blood-borne infections including human immunodeficiency virus (HIV), hepatitis C virus (HCV), hepatitis B virus (HBV) and a number of sexually transmitted infections. These infections can spread among IDUs via risky sexual and needle-sharing contacts. To accurately model the spread of such contagions among IDUs, we build a bi-layer network that captures both types of risky contacts. We present methodology for inferring important model parameters, such as those governing network structure and dynamics, from readily available data sources (e.g., epidemiological surveys). Such a model can be used to evaluate the efficacy of various programs that aim to combat drug addiction and contain blood-borne diseases among IDUs. The model is especially useful for evaluating interventions that exploit the structure of the contact network. To illustrate, we instantiate a network model with data collected by a needle and syringe program in Chicago. We model sexual and needle-sharing contacts and the consequent spread of HIV and HCV. We use the model to evaluate the potential effects of a peer education (PE) program under different targeting strategies. We show that a targeted PE program would avert significantly more HIV and HCV infections than an untargeted program, highlighting the importance of reaching individuals who are centrally located in contact networks when instituting prevention programs.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Epidemic; Injection drug user; Network model; Parameter inference; Stochastic simulation

Mesh:

Year:  2016        PMID: 26775738      PMCID: PMC5154253          DOI: 10.1016/j.mbs.2016.01.003

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   3.935


  72 in total

1.  Sociometric risk networks and risk for HIV infection.

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2.  Correlates of consistent condom use with main partners by partnership patterns among young adult male injection drug users from five US cities.

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4.  Comparison of progression and non-progression in injecting drug users and homosexual men with documented dates of HIV-1 seroconversion. European Seroconverter Study and the Tricontinental Seroconverter Study.

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8.  Outcome of screening for hepatitis C virus infection based on risk factors.

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9.  Peginterferon-alpha2a and ribavirin combination therapy in chronic hepatitis C: a randomized study of treatment duration and ribavirin dose.

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10.  Prevalence of hepatitis C virus infection among injection drug users in the United States, 1994-2004.

Authors:  Joseph J Amon; Richard S Garfein; Linda Ahdieh-Grant; Gregory L Armstrong; Lawrence J Ouellet; Mary H Latka; David Vlahov; Steffanie A Strathdee; Sharon M Hudson; Peter Kerndt; Don Des Jarlais; Ian T Williams
Journal:  Clin Infect Dis       Date:  2008-06-15       Impact factor: 9.079

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Review 1.  Mathematical modeling of hepatitis c virus (HCV) prevention among people who inject drugs: A review of the literature and insights for elimination strategies.

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2.  Cost-effectiveness of alternative strategies for provision of HIV preexposure prophylaxis for people who inject drugs.

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Review 4.  A review of network simulation models of hepatitis C virus and HIV among people who inject drugs.

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Journal:  Int J Drug Policy       Date:  2019-11-15

5.  Predicting the Effectiveness of Endemic Infectious Disease Control Interventions: The Impact of Mass Action versus Network Model Structure.

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Journal:  Med Decis Making       Date:  2021-04-24       Impact factor: 2.749

6.  Country versus pharmaceutical company interests for hepatitis C treatment.

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  6 in total

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