Nicholson, George and Blangiardo, Marta and Briers, Mark and Diggle, Peter J. and Fjelde, Tor Erlend and Ge, Hong and Goudie, Robert J. B. and Jersakova, Radka and King, Ruairidh E. and Lehmann, Brieuc C. L. and Mallon, Ann-Marie and Padellini, Tullia and Teh, Yee Whye and Holmes, Chris and Richardson, Sylvia (2022) Interoperability of Statistical Models in Pandemic Preparedness:Principles and Reality. Statistical Science, 37 (2). pp. 183-206. ISSN 0883-4237
Full text not available from this repository.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.