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Demonstrating multi-country calibration of a tuberculosis model using new history matching and emulation package - hmer

Scarponi, Danny; Iskauskas, Andrew; Clark, Rebecca A; Vernon, Ian; McKinley, Trevelyan J.; Goldstein, Michael; Mukandavire, Christinah; Deol, Arminder; Weerasuriya, Chathika; Bakker, Roel; White, Richard G; McCreesh, Nicky

Demonstrating multi-country calibration of a tuberculosis model using new history matching and emulation package - hmer Thumbnail


Authors

Danny Scarponi

Rebecca A Clark

Trevelyan J. McKinley

Christinah Mukandavire

Arminder Deol

Chathika Weerasuriya

Roel Bakker

Richard G White

Nicky McCreesh



Abstract

Infectious disease models are widely used by epidemiologists to improve the understanding of transmission dynamics and disease natural history, and to predict the possible effects of interventions. As the complexity of such models increases, however, it becomes increasingly challenging to robustly calibrate them to empirical data. History matching with emulation is a calibration method that has been successfully applied to such models, but has not been widely used in epidemiology partly due to the lack of available software. To address this issue, we developed a new, user-friendly R package hmer to simply and efficiently perform history matching with emulation. In this paper, we demonstrate the first use of hmer for calibrating a complex deterministic model for the country-level implementation of tuberculosis vaccines to 115 low- and middle-income countries. The model was fit to 9–13 target measures, by varying 19–22 input parameters. Overall, 105 countries were successfully calibrated. Among the remaining countries, hmer visualisation tools, combined with derivative emulation methods, provided strong evidence that the models were misspecified and could not be calibrated to the target ranges. This work shows that hmer can be used to simply and rapidly calibrate a complex model to data from over 100 countries, making it a useful addition to the epidemiologist’s calibration tool-kit.

Citation

Scarponi, D., Iskauskas, A., Clark, R. A., Vernon, I., McKinley, T. J., Goldstein, M., …McCreesh, N. (2023). Demonstrating multi-country calibration of a tuberculosis model using new history matching and emulation package - hmer. Epidemics, 43, Article 100678. https://doi.org/10.1016/j.epidem.2023.100678

Journal Article Type Article
Acceptance Date Mar 6, 2023
Online Publication Date Mar 7, 2023
Publication Date 2023-06
Deposit Date Mar 10, 2023
Publicly Available Date May 30, 2023
Journal Epidemics
Print ISSN 1755-4365
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 43
Article Number 100678
DOI https://doi.org/10.1016/j.epidem.2023.100678
Public URL https://durham-repository.worktribe.com/output/1179036

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