A mathematical model for HIV and hepatitis C co-infection and its assessment from a statistical perspective

Amparo Yovanna Castro Sanchez, Marc Aerts, Ziv Shkedy, Peter Vickerman, Fabrizio Faggiano, Guiseppe Salamina, Niel Hens

Research output: Contribution to journalArticle (Academic Journal)peer-review

14 Citations (Scopus)

Abstract

The hepatitis C virus (HCV) and the human immunodeficiency virus (HIV) are a clear threat for public health, with high prevalences especially in high risk groups such as injecting drug users. People with HIV infection who are also infected by HCV suffer from a more rapid progression to HCV-related liver disease and have an increased risk for cirrhosis and liver cancer. Quantifying the impact of HIV and HCV co-infection is therefore of great importance. We propose a new joint mathematical model accounting for co-infection with the two viruses in the context of injecting drug users (IDUs). Statistical concepts and methods are used to assess the model from a statistical perspective, in order to get further insights in: (i) the comparison and selection of optional model components, (ii) the unknown values of the numerous model parameters, (iii) the parameters to which the model is most 'sensitive' and (iv) the combinations or patterns of values in the high-dimensional parameter space which are most supported by the data. Data from a longitudinal study of heroin users in Italy are used to illustrate the application of the proposed joint model and its statistical assessment. The parameters associated with contact rates (sharing syringes) and the transmission rates per syringe-sharing event are shown to play a major role.

Original languageEnglish
Pages (from-to)56-66
Number of pages11
JournalEpidemics
Volume5
Issue number1
DOIs
Publication statusPublished - Mar 2013

Bibliographical note

Copyright © 2013 Elsevier B.V. All rights reserved.

Keywords

  • Coinfection
  • Computer Simulation
  • HIV Infections
  • Hepacivirus
  • Hepatitis C
  • Humans
  • Italy
  • Liver Cirrhosis
  • Liver Neoplasms
  • Models, Theoretical
  • Needle Sharing
  • Prevalence
  • Risk Factors
  • Substance Abuse, Intravenous

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