A priori prediction of disease invasion dynamics in a novel environment

Colin A. Russell, David L. Smith, Lance A. Waller, James E. Childs, Leslie A. Real

Research output: Contribution to journalArticlepeer-review

Abstract

Directly transmitted infectious diseases spread through wildlife populations as travelling waves away from the sites of original introduction. These waves often become distorted through their interaction with environmental and population heterogeneities and by long-distance translocation of infected individuals. Accurate a priori predictions of travelling waves of infection depend upon understanding and quantifying these distorting factors. We assess the effects of anisotropies arising from the orientation of rivers in relation to the direction of disease-front propagation and the damming effect of mountains on disease movement in natural populations. The model successfully predicts the local and large-scale pre-vaccination spread of raccoon rabies through New York State, based on a previous spatially heterogeneous model of raccoon-rabies invasion across the state of Connecticut. Use of this model provides a rare example of a priori prediction of an epidemic invasion over a naturally heterogeneous landscape. Model predictions matched to data can also be used to evaluate the most likely points of disease introduction. These results have general implications for predicting future pathogen invasions and evaluating potential containment strategies.

Original languageEnglish (US)
Pages (from-to)21-25
Number of pages5
JournalProceedings of the Royal Society B: Biological Sciences
Volume271
Issue number1534
DOIs
StatePublished - Jan 7 2004
Externally publishedYes

Keywords

  • Disease invasion
  • Disease population dynamics
  • Emerging infectious diseases
  • Rabies
  • Spatial epidemics

ASJC Scopus subject areas

  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)

Fingerprint

Dive into the research topics of 'A priori prediction of disease invasion dynamics in a novel environment'. Together they form a unique fingerprint.

Cite this