Bayesian emulation and history matching of JUNE.
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ABSTRACT:
SUBMITTER: Vernon I
PROVIDER: S-EPMC9376712 | biostudies-literature | 2022 Oct
REPOSITORIES: biostudies-literature
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Bayesian emulation and history matching of JUNE.
Vernon I I Owen J J Aylett-Bullock J J Cuesta-Lazaro C C Frawley J J Quera-Bofarull A A Sedgewick A A Shi D D Truong H H Turner M M Walker J J Caulfield T T Fong K K Krauss F F
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 20220815 2233
We analyze JUNE: a detailed model of COVID-19 transmission with high spatial and demographic resolution, developed as part of the RAMP initiative. JUNE requires substantial computational resources to evaluate, making model calibration and general uncertainty analysis extremely challenging. We describe and employ the uncertainty quantification approaches of Bayes linear emulation and history matching to mimic JUNE and to perform a global parameter search, hence identifying regions of parameter sp ...[more]
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