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Elsevier, Epidemics, (10), p. 83-87, 2015

DOI: 10.1016/j.epidem.2014.09.004

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Four key challenges in infectious disease modelling using data from multiple sources

Journal article published in 2015 by Daniela De Angelis ORCID, Presanis Am, Anne M. Presanis, Paul J. Birrell ORCID, Birrell Pj, Gianpaolo Scalia Tomba, Thomas House
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Public health-related decision-making on policies aimed at controlling epidemics is increasingly evidence-based, exploiting multiple sources of data. Policy makers rely on complex models that are required to be robust, realistically approximating epidemics and consistent with all relevant data. Meeting these requirements in a statistically rigorous and defendable manner poses a number of challenging problems. How to weight evidence from different datasets and handle dependence between them, efficiently estimate and critically assess complex models are key challenges that we expound in this paper, using examples from influenza modelling.