History matching of a complex epidemiological model of HIV transmission using variance emulation
Andrianakis, I; Vernon, I; McCreesh, N; et al.McKinley, TJ; Oakley, J; Nsubuga, R; Goldstein, M; White, R
Date: 24 November 2016
Journal
Journal of the Royal Statistical Society Series C: Applied Statistics
Publisher
Wiley for Royal Statistical Society
Publisher DOI
Abstract
Complex stochastic models are commonplace in epidemiology, but their utility depends on their
calibration to empirical data. History matching is a (pre-)calibration method that has been applied
successfully to complex deterministic models. In this work, we adapt history matching to stochastic
models, by emulating the variance in the ...
Complex stochastic models are commonplace in epidemiology, but their utility depends on their
calibration to empirical data. History matching is a (pre-)calibration method that has been applied
successfully to complex deterministic models. In this work, we adapt history matching to stochastic
models, by emulating the variance in the model outputs, and therefore accounting for its dependence
on the model’s input values. The proposed method is applied to a real complex epidemiological model
of HIV in Uganda with 22 inputs and 18 outputs, and is found to increase the efficiency of history
matching, requiring 70% of the time and 43% fewer simulator evaluations compared to a previous
variant of the method. The insight gained into the structure of the HIV model, and the constraints
placed upon it, are then discussed.
Mathematics and Statistics
Faculty of Environment, Science and Economy
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