Using information theory to optimise epidemic models for real-time prediction and estimation

Kris V. Parag; Christl A. Donnelly

doi:10.1371/journal.pcbi.1007990

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Open Access

Peer-reviewed

Research Article

Using information theory to optimise epidemic models for real-time prediction and estimation

Kris V. Parag ,

Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Writing – original draft, Writing – review & editing

* E-mail: k.parag@imperial.ac.uk

Affiliation MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, United Kingdom

http://orcid.org/0000-0002-7806-3605

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Christl A. Donnelly

Roles Supervision, Validation, Writing – review & editing

Affiliations MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, United Kingdom, Department of Statistics, University of Oxford, Oxford, OX1 3LB, United Kingdom

http://orcid.org/0000-0002-0195-2463

⨯

Using information theory to optimise epidemic models for real-time prediction and estimation

Kris V. Parag,
Christl A. Donnelly

Published: July 1, 2020
https://doi.org/10.1371/journal.pcbi.1007990

About the Authors

Kris V. Parag

Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Writing – original draft, Writing – review & editing

* E-mail: k.parag@imperial.ac.uk

Affiliation MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, United Kingdom

http://orcid.org/0000-0002-7806-3605

Christl A. Donnelly

Roles Supervision, Validation, Writing – review & editing

Affiliations MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, W2 1PG, United Kingdom, Department of Statistics, University of Oxford, Oxford, OX1 3LB, United Kingdom

http://orcid.org/0000-0002-0195-2463

Competing Interests

The authors have declared that no competing interests exist.

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Epidemiology
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Infectious disease epidemiology
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Influenza
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Forecasting
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Population dynamics
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SARS
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Graphs
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Infectious diseases
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