Repository logo
 

Interoperability of statistical models in pandemic preparedness: principles and reality

Published version
Peer-reviewed

Change log

Authors

Nicholson, George 
Blangiardo, Marta 
Briers, Mark 
Diggle, Peter J 
Fjelde, Tor Erlend 

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.

Description

Keywords

stat.ME, stat.ME, stat.AP, 62P10

Journal Title

Statistical Science

Conference Name

Journal ISSN

0883-4237
2168-8745

Volume Title

Publisher

Institute of Mathematical Statistics
Sponsorship
Engineering and Physical Sciences Research Council (EP/R018561/1)
MRC (Unknown)
MRC (unknown)
EPSRC (EP/W002965/1)