Andrianakis, I. and Vernon, I. and McCreesh, N. and McKinley, T. J. and Oakley, J. E. and Nsubuga, R. N. and Goldstein, M. and White, R. G. (2017) 'History matching of a complex epidemiological model of human immunodeficiency virus transmission by using variance emulation.', Journal of the Royal Statistical Society : series C (applied statistics)., 66 (4). pp. 717-740.
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 method proposed is applied to a real complex epidemiological model of human immunodeficiency virus 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 with a previous variant of the method. The insight gained into the structure of the human immunodeficiency virus model, and the constraints placed on it, are then discussed.
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|Publisher Web site:||https://doi.org/10.1111/rssc.12198|
|Publisher statement:||© 2017 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.|
|Date accepted:||01 October 2016|
|Date deposited:||25 July 2017|
|Date of first online publication:||24 November 2016|
|Date first made open access:||25 July 2017|
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