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dc.contributor.authorScarponi, D
dc.contributor.authorIskauskas, A
dc.contributor.authorClark, RA
dc.contributor.authorVernon, I
dc.contributor.authorMcKinley, TJ
dc.contributor.authorGoldstein, M
dc.contributor.authorMukandavire, C
dc.contributor.authorDeol, A
dc.contributor.authorWeerasuriya, C
dc.contributor.authorBakker, R
dc.contributor.authorWhite, RG
dc.contributor.authorMcCreesh, N
dc.date.accessioned2023-11-29T11:14:59Z
dc.date.issued2023-03-07
dc.date.updated2023-11-29T10:52:11Z
dc.description.abstractInfectious 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.en_GB
dc.description.sponsorshipWellcome Trusten_GB
dc.description.sponsorshipWorld Health Organization (WHO)en_GB
dc.description.sponsorshipNational Institutes of Health (NIH)en_GB
dc.description.sponsorshipEDTCPen_GB
dc.description.sponsorshipMedical Research Council (MRC)en_GB
dc.description.sponsorshipEconomic and Social Research Council (ESRC)en_GB
dc.description.sponsorshipBill & Melinda Gates Foundationen_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.description.sponsorshipResearch Englanden_GB
dc.identifier.citationVol. 43, article 100678en_GB
dc.identifier.doihttps://doi.org/10.1016/j.epidem.2023.100678
dc.identifier.grantnumber218261/Z/19/Zen_GB
dc.identifier.grantnumber2020/985800-0en_GB
dc.identifier.grantnumber1R01AI147321-01en_GB
dc.identifier.grantnumberRIA208D-2505Ben_GB
dc.identifier.grantnumberCCF17-7779 via SET Bloomsburyen_GB
dc.identifier.grantnumberES/P008011/1en_GB
dc.identifier.grantnumberOPP1084276en_GB
dc.identifier.grantnumberOPP1135288en_GB
dc.identifier.grantnumberINV-001754en_GB
dc.identifier.grantnumberINV-001754en_GB
dc.identifier.grantnumberEP W011956en_GB
dc.identifier.urihttp://hdl.handle.net/10871/134686
dc.identifierORCID: 0000-0002-9485-3236 (McKinley, Trevelyan J)
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pubmed/36913805en_GB
dc.rights© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectMathematical modellingen_GB
dc.subjectModel calibrationen_GB
dc.subjectTuberculosisen_GB
dc.subjectVaccinesen_GB
dc.titleDemonstrating multi-country calibration of a tuberculosis model using new history matching and emulation package - hmeren_GB
dc.typeArticleen_GB
dc.date.available2023-11-29T11:14:59Z
dc.identifier.issn1755-4365
exeter.article-number100678
exeter.place-of-publicationNetherlands
dc.descriptionThis is the final version. Available on open access from Elsevier via the DOI in this record. en_GB
dc.identifier.eissn1878-0067
dc.identifier.journalEpidemicsen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2023-03-06
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2023-03-07
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-11-29T11:07:24Z
refterms.versionFCDVoR
refterms.dateFOA2023-11-29T11:15:06Z
refterms.panelAen_GB
refterms.dateFirstOnline2023-03-07


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© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).