Mathematical and Statistical Models for HIV and Co-Infections (R-1327)

The Amsterdam Cohort Studies is a longitudinal survey in which the main responses are time to HIV and hepatitis C (HCV) infection in Injecting Drug Users. The Nonparametric Maximum Likelihood Estimator, and the logspline estimator will be used to estimate the survival curve and the hazard curve for several subsets of the data. Several parametric models with and without covariates while assessing goodness of fit will be fitted. A second research topic is the analysis of a Probiotics study where the main objective is to extend the interval censored survival methodology to time dependent covariates. The project is a prospective cohort study which investigates the effect of probiotics on the acquisition of intestinal colonization of hospital-associated bacterium Ampicillin-Resistant Enterococcus faecium (ARE). A group of patients received probiotics for some days during the follow up time. The objective is to assess the impact of the probiotics and several other covariates (including time varying covariates such as colonization pressure, isolation and use of antibiotics). A third topic is the phylogenetics analysis of the hepatitis C virus (HCV). This topic looks at HCV from a different perspective, here the main input is provided by Injecting Drug Users from Belgium who are already infected with the virus. Each IDU participant in the study, who is positive for HCV, provides a DNA sequence of the virus. With the DNA sequences, the effective number of species in a period of time is calculated; this is called the classical skyline plot. The main research objective is to fit several statistical models to the classical skyline plots.

Keywords:INTERVAL CENSORING, MODELS FOR COINFECTION HIV & HCV, NONPARAMETRIC ESTIMATION, PHYLOGENETIC ANALYSIS

Disciplines:Information and computing sciences, Biological sciences, Computer engineering, information technology and mathematical engineering, Basic sciences, Clinical sciences, Health sciences, Translational sciences