Phylogenetic and epidemic modeling of rapidly evolving infectious diseases
Phylogenetic and epidemic modeling of rapidly evolving infectious diseases
Epidemic modeling of infectious diseases has a long history in both theoretical and empirical research. However the recent explosion of genetic data has revealed the rapid rate of evolution that many populations of infectious agents undergo and has underscored the need to consider both evolutionary and ecological processes on the same time scale. Mathematical epidemiology has applied dynamical models to study infectious epidemics, but these models have tended not to exploit – or take into account – evolutionary changes and their effect on the ecological processes and population dynamics of the infectious agent. On the other hand, statistical phylogenetics has increasingly been applied to the study of infectious agents. This approach is based on phylogenetics, molecular clocks, genealogy-based population genetics and phylogeography. Bayesian Markov chain Monte Carlo and related computational tools have been the primary source of advances in these statistical phylogenetic approaches. Recently the first tentative steps have been taken to reconcile these two theoretical approaches. We survey the Bayesian phylogenetic approach to epidemic modeling of infection diseases and describe the contrasts it provides to mathematical epidemiology as well as emphasize the significance of the future unification of these two fields.
1825-1841
Kühnert, Denise
ec21eb4a-ba28-4a35-8f74-04ec1edb7552
Wu, Chieh-Hsi
ace630c6-2095-4ade-b657-241692f6b4d3
Drummond, Alexei J.
9178c794-fbc9-4f0b-b63d-44b724848223
December 2011
Kühnert, Denise
ec21eb4a-ba28-4a35-8f74-04ec1edb7552
Wu, Chieh-Hsi
ace630c6-2095-4ade-b657-241692f6b4d3
Drummond, Alexei J.
9178c794-fbc9-4f0b-b63d-44b724848223
Kühnert, Denise, Wu, Chieh-Hsi and Drummond, Alexei J.
(2011)
Phylogenetic and epidemic modeling of rapidly evolving infectious diseases.
Infection, Genetics and Evolution, 11 (8), .
(doi:10.1016/j.meegid.2011.08.005).
Abstract
Epidemic modeling of infectious diseases has a long history in both theoretical and empirical research. However the recent explosion of genetic data has revealed the rapid rate of evolution that many populations of infectious agents undergo and has underscored the need to consider both evolutionary and ecological processes on the same time scale. Mathematical epidemiology has applied dynamical models to study infectious epidemics, but these models have tended not to exploit – or take into account – evolutionary changes and their effect on the ecological processes and population dynamics of the infectious agent. On the other hand, statistical phylogenetics has increasingly been applied to the study of infectious agents. This approach is based on phylogenetics, molecular clocks, genealogy-based population genetics and phylogeography. Bayesian Markov chain Monte Carlo and related computational tools have been the primary source of advances in these statistical phylogenetic approaches. Recently the first tentative steps have been taken to reconcile these two theoretical approaches. We survey the Bayesian phylogenetic approach to epidemic modeling of infection diseases and describe the contrasts it provides to mathematical epidemiology as well as emphasize the significance of the future unification of these two fields.
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Accepted/In Press date: 9 August 2011
e-pub ahead of print date: 31 August 2011
Published date: December 2011
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Local EPrints ID: 437885
URI: http://eprints.soton.ac.uk/id/eprint/437885
ISSN: 1567-1348
PURE UUID: c75492bf-0c43-4dc3-965e-b0bda5f8672b
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Date deposited: 21 Feb 2020 17:31
Last modified: 17 Mar 2024 04:00
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Author:
Denise Kühnert
Author:
Alexei J. Drummond
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