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Modelling sexual transmission of HIV: testing the assumptions, validating the predictions
Rebecca F Baggaley1, Christophe Fraser
1Department of Infectious Disease Epidemiology, MRC Centre for Outbreak Analysis and Modelling, Imperial College London, London, UK. r.baggaley@imperial.ac.uk
Purpose Of Review:
To discuss the role of mathematical models of sexual transmission of HIV: the methods used and their impact.
Recent Findings:
We use mathematical modelling of 'universal test and treat' as a case study to illustrate wider issues relevant to all modelling of sexual HIV transmission.
Summary:
Mathematical models are used extensively in HIV epidemiology to deduce the logical conclusions arising from one or more sets of assumptions. Simple models lead to broad qualitative understanding, whereas complex models can encode more realistic assumptions and, thus, be used for predictive or operational purposes. An overreliance on model analysis in which assumptions are untested and input parameters cannot be estimated should be avoided. Simple models providing bold assertions have provided compelling arguments in recent public health policy, but may not adequately reflect the uncertainty inherent in the analysis.
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