Interoperability of statistical models in pandemic preparedness: principles and reality.

Nicholson G., Blangiardo M., Briers M., Diggle PJ., Fjelde TE., Ge H., Goudie RJB., Jersakova R., King RE., Lehmann BCL., Mallon A-M., Padellini T., Teh YW., Holmes C., Richardson S.

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.

DOI

10.1214/22-sts854

Type

Journal article

Journal

Statistical science : a review journal of the Institute of Mathematical Statistics

Publication Date

05/2022

Volume

37

Pages

183 - 206

Addresses

University of Oxford, UK.

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