4.5 Article

An agent-based model of red colobus resources and disease dynamics implicates key resource sites as hot spots of disease transmission

Journal

ECOLOGICAL MODELLING
Volume 221, Issue 20, Pages 2491-2500

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecolmodel.2010.07.020

Keywords

Red colobus; Spatially explicit agent-based model; SEIR model; Disease transmission; Kibale National Park; Uganda

Categories

Funding

  1. Canada Research Chairs Program
  2. Wildlife Conservation Society
  3. Natural Science and Engineering Research Council of Canada
  4. National Geographic
  5. National Science Foundation
  6. Morris Animal Foundation [D07ZO-024]
  7. University of Wisconsin School of Medicine and Public Health
  8. Natural Science and Engineering Research Council of Canada (RS, CC)

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The effect of anthropogenic landscape change on disease in wildlife populations represents a growing conservation and public health concern. Red colobus monkeys (Procolobus rufomitratus), an endangered primate species, are particularly susceptible to habitat alteration and have been the focus of a great deal of disease and ecological research as a result. To infer how landscape changes can affect host and parasite dynamics, a spatially explicit agent-based model is created to simulate movement and foraging of this primate, based on a resource landscape estimated from extensive plot-derived tree population data from Kibale National Park, Uganda. Changes to this resource landscape are used to simulate effects of anthropogenic forest change. With each change in the landscape, disease outcomes within the simulated red colobus population are monitored using a hypothetical microparasite with a directly transmitted life cycle. The model predicts an optimal distribution of resources which facilitates the spread of an infectious agent through the simulated population. The density of resource rich sites and the overall heterogeneity of the landscape are important factors contributing to this spread. The characteristics of this optimal distribution are similar to those of logged sections of forest adjacent to our study area. (C) 2010 Elsevier B.V. All rights reserved.

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