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Capturing escape in infectious disease dynamics

by: Sarah Cobey, and Katia Koelle

In: Trends in Ecology & Evolution, Vol. 23, Nr. 10 (2008) , p. 572 - 577.

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URL:	http://www.sciencedirect.com/science/article/B6VJ1-4T8006R-2/2/adee7c9c8a6091d943389db19e5d5047
DOI:	10.1016/j.tree.2008.06.008

Identifying the causes of interannual variability in disease dynamics is important for understanding and managing epidemics. Traditionally, these causes have been classified as intrinsic e.g. immunity fluctuations or extrinsic e.g. climate forcing; ecologists determine the relative contributions of these factors by applying statistical models to time series of cases. Here we address the problem of isolating the drivers of pathogen dynamics that are influenced by antigenic evolution. Recent findings indicate that many pathogens escape immunity in a punctuated manner; for them, we argue that time series of cases alone will be insufficient to isolate causal drivers. We detail observations that can reveal the presence of punctuated immune escape, and which can be used in new statistical approaches to identify extrinsic and intrinsic regulators of disease.

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ScienceDirect - Trends in Ecology & Evolution : Capturing escape in infectious disease dynamics

BibTeX record

@article{Cobey2008572,
  abstract = {Identifying the causes of interannual variability in disease dynamics is important for understanding and managing epidemics. Traditionally, these causes have been classified as intrinsic (e.g. immunity fluctuations) or extrinsic (e.g. climate forcing); ecologists determine the relative contributions of these factors by applying statistical models to time series of cases. Here we address the problem of isolating the drivers of pathogen dynamics that are influenced by antigenic evolution. Recent findings indicate that many pathogens escape immunity in a punctuated manner; for them, we argue that time series of cases alone will be insufficient to isolate causal drivers. We detail observations that can reveal the presence of punctuated immune escape, and which can be used in new statistical approaches to identify extrinsic and intrinsic regulators of disease.},
  added-at = {2009-07-03T22:48:49.000+0200},
  author = {Cobey, Sarah and Koelle, Katia},
  biburl = {http://www.bibsonomy.org/bibtex/25928e9a51e1f3fb5f46ee77419a146b4/ebo},
  description = {ScienceDirect - Trends in Ecology & Evolution : Capturing escape in infectious disease dynamics},
  doi = {DOI: 10.1016/j.tree.2008.06.008},
  interhash = {204e1d840a0f3b60a4f3f65223a43823},
  intrahash = {5928e9a51e1f3fb5f46ee77419a146b4},
  issn = {0169-5347},
  journal = {Trends in Ecology & Evolution},
  keywords = {epi evolution imported printed review},
  number = 10,
  pages = {572 - 577},
  timestamp = {2009-07-03T22:48:49.000+0200},
  title = {Capturing escape in infectious disease dynamics},
  url = {http://www.sciencedirect.com/science/article/B6VJ1-4T8006R-2/2/adee7c9c8a6091d943389db19e5d5047},
  volume = 23,
  year = 2008
}

Endnote record

%0 Journal Article
%1 Cobey2008572
%A Cobey, Sarah
%A Koelle, Katia
%D 2008
%J Trends in Ecology & Evolution
%K 
%N 10
%P 572 - 577
%T Capturing escape in infectious disease dynamics
%R DOI: 10.1016/j.tree.2008.06.008
%U http://www.sciencedirect.com/science/article/B6VJ1-4T8006R-2/2/adee7c9c8a6091d943389db19e5d5047
%V 23
%X Identifying the causes of interannual variability in disease dynamics is important for understanding and managing epidemics. Traditionally, these causes have been classified as intrinsic (e.g. immunity fluctuations) or extrinsic (e.g. climate forcing); ecologists determine the relative contributions of these factors by applying statistical models to time series of cases. Here we address the problem of isolating the drivers of pathogen dynamics that are influenced by antigenic evolution. Recent findings indicate that many pathogens escape immunity in a punctuated manner; for them, we argue that time series of cases alone will be insufficient to isolate causal drivers. We detail observations that can reveal the presence of punctuated immune escape, and which can be used in new statistical approaches to identify extrinsic and intrinsic regulators of disease.