Phylogenetic and epidemic modeling of rapidly evolving infectious diseases

Denise Kühnert, Chieh Hsi Wu, Alexei J. Drummond

Research output: Contribution to journalArticle

39 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1825-1841
Number of pages17
JournalInfection, Genetics and Evolution
Volume11
Issue number8
DOIs
Publication statusPublished - Dec 2011
Externally publishedYes

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Keywords

  • Coalescent
  • Phylodynamics
  • Phylogenetic epidemiology
  • Rapidly evolving viruses
  • Statistical phylogeography
  • Stochastic SIR

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Molecular Biology
  • Microbiology
  • Infectious Diseases
  • Microbiology (medical)

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