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An Isaac Newton Institute Workshop

Stochastic Computation for the Analysis of Ecological and Epidemiological Data

MODELING TUBERCULOSIS IN AREAS OF HIGH HIV PREVALENCE

Authors: Georgina R. Hughes (University of Southampton), Christine S. M. Currie (University of Southampton), Elizabeth L. Corbett (London School of Hygiene and Tropical Medicine & Biomedical Research and Training Institute, Harare, Zimbabwe)

Abstract

We describe a discrete event simulation model of tuberculosis (TB) and HIV disease, parameterized to describe the dual epidemics in Harare, Zimbabwe. TB and HIV are the leading causes of death from infectious disease among adults worldwide and the number of TB cases has risen significantly since the start of the HIV epidemic, particu-larly in Sub-Saharan Africa, where the HIV epidemic is most severe. There is a need to devise new strategies for TB control in countries with a high prevalence of HIV. This model has been designed to investigate strategies for reducing TB transmission by more efficient TB case detection. The model structure and its validation are discussed.