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Interoperability of statistical models in pandemic preparedness: principles and reality
George Nicholson1, Marta Blangiardo2, Mark Briers1,2,3,4,5,6,7,8,9
1University of Oxford, UK.
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 and characterising spatial-temporal prevalence and reproduction numbers of SARS-CoV-2 infections in England.
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