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Interoperability of Statistical Models in Pandemic Preparedness: Principles and Reality

Nicholson, George; Blangiardo, Marta; Briers, Mark; Diggle, Peter J; Fjelde, Tor Erlend; Ge, Hong; Goudie, Robert JB; ... Richardson, Sylvia; + view all (2022) Interoperability of Statistical Models in Pandemic Preparedness: Principles and Reality. Statistical Science , 37 (2) pp. 183-206. 10.1214/22-STS854. Green open access

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Abstract

We present "interoperability" as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving pandemic response. Interoperability provides an important set of principles for future pandemic preparedness, through the joint design and deployment of adaptable systems of statistical models for disease surveillance using probabilistic reasoning. We illustrate this through case studies for inferring spatial-temporal coronavirus disease 2019 (COVID-19) prevalence and reproduction numbers in England.

Type: Article
Title: Interoperability of Statistical Models in Pandemic Preparedness: Principles and Reality
Open access status: An open access version is available from UCL Discovery
DOI: 10.1214/22-STS854
Publisher version: https://doi.org/10.1214/22-STS854
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third-party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Keywords: Science & Technology, Physical Sciences, Statistics & Probability, Mathematics, Bayesian graphical models, Bayesian melding, COVID-19, evidence synthesis, interoperability, modularization, multi-source inference, EPIDEMIOLOGY, PREVALENCE, SARS-COV-2, INFECTION, INFERENCE, ENGLAND
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10149944
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