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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14757

Title: A mathematical model for HIV and hepatitis C co-infection and its assessment from a statistical
Authors: Castro Sanchez, Amparo Yovanna
Aerts, Marc
Shkedy, Ziv
Vickerman, Peter
Faggiano, Fabrizio
Salamina, Giuseppe
Hens, Niel
Issue Date: 2013
Citation: Epidemics, 5 (1), p. 56-66
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.
Notes: Highlights: We propose a model for HIV and HCV co-infection for injecting drug users. We present statistical concepts and methods to assess the mathematical model. The model considers biological complexities in the transmission of HCV and HIV. The methods are applied to data from a longitudinal study of heroin users in Italy. Sharing syringes rates and transmission probabilities rates play a major role.
URI: http://hdl.handle.net/1942/14757
DOI: 10.1016/j.epidem.2013.01.002
ISI #: 000315356200006
ISSN: 1755-4365
Category: A1
Type: Journal Contribution
Validation: ecoom, 2014
Appears in Collections: Research publications

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