Dynamic Modeling of Herpes Simplex Virus Type-2 (HSV-2) Transmission: Issues in Structural Uncertainty.

Foss, AM; Vickerman, PT; Chalabi, Z; Mayaud, P; Alary, M; Watts, CH; (2009) Dynamic Modeling of Herpes Simplex Virus Type-2 (HSV-2) Transmission: Issues in Structural Uncertainty. Bulletin of mathematical biology, 71 (3). pp. 720-49. ISSN 0092-8240 DOI: https://doi.org/10.1007/s11538-008-9379-1

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The sexually transmitted infection (STI) Herpes simplex virus type-2 (HSV-2) is of public health concern because it is a very common frequently unrecognized lifelong infection, which may facilitate HIV transmission. Within HIV/STI modeling, structural uncertainty has received less attention than parametric uncertainty. By merging the compartments of a "complex" model, a "simple" HSV-2 model is developed. Sexual interactions between female sex workers (FSWs) and clients are modeled using data from India. Latin Hypercube Sampling selects from parameter distributions and both models are run for each of the 10,000 parameter sets generated. Outputs are compared (except for 2,450 unrealistic simulations). The simple model is a good approximation to the complex model once the HSV-2 epidemic has reached 60% of the equilibrium prevalence (95% of the 7,550 runs produced <10% relative error). The simple model is a reduced version of the complex model that retains details implicitly. For late-stage epidemics, the simple model gives similar prevalence trends to the complex model. As HSV-2 epidemics in many populations are advanced, the simple model is accurate in most instances, although the complex model may be preferable for early epidemics. The analysis highlights the issue of structural uncertainty and the value of reducing complexity.

Item Type: Article
Faculty and Department: Faculty of Infectious and Tropical Diseases > Dept of Clinical Research
Faculty of Public Health and Policy > Dept of Global Health and Development
Faculty of Public Health and Policy > Dept of Social and Environmental Health Research
Research Centre: Centre for Maternal, Reproductive and Child Health (MARCH)
Social and Mathematical Epidemiology (SaME)
PubMed ID: 19219511
Web of Science ID: 264092300009
URI: http://researchonline.lshtm.ac.uk/id/eprint/5784


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