Baguelin, Marc

Buckingham-Jeffery, Elizabeth

Hall, Ian

House, Thomas

Kinyanjui, Timothy Muiruri

Pellis, Lorenzo

Often, the task of epidemiological modelling is seen as one of im- proving biological and social realism, with increasing data availabil- ity enabling increased realism. Here, we consider ways in which models designed to support policy have di erent data and algorith- mic requirements from those aiming at realism or insight, via a series of case studies. In particular, calculation and communication of uncertainty is often more important than re nement of model structure without con rmation of validity

Epidemiological Data and Model Requirements to Support Policy

Abstract

Similar works

Full text

Available Versions

The University of Manchester - Institutional Repository