ArticleJournal of the Royal Statistical Society. Series C, Applied statistics2017
History matching of a complex epidemiological model of human immunodeficiency virus transmission by using variance emulation.
Article in Journal of the Royal Statistical Society. Series C, Applied statistics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Systematic structural discrepancy assessment for computer models.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Incorporating social determinants of health into agent-based models of HIV transmission: methodological challenges and future directions.Frontiers in epidemiology · 2025Review
- The Constrained Disorder Principle Overcomes the Challenges of Methods for Assessing Uncertainty in Biological Systems.Journal of personalized medicine · 2024Review
- New tuberculosis vaccines in India: modelling the potential health and economic impacts of adolescent/adult vaccination with M72/AS01BMC medicine · 2023Article
- Bayesian emulation and history matching of JUNE.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022Article
- June: open-source individual-based epidemiology simulation.Royal Society open science · 2021Article
- The use of mixture density networks in the emulation of complex epidemiological individual-based models.PLoS computational biology · 2020Article
- Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions.BMC systems biology · 2018Article
Corrections and comments
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Authors and funding
8 authors.
Funding
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 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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Registered trials
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