• Open Access

Modelling malaria pathogenesis

Authors

  • Nicole Mideo,

    Corresponding author
    1. Department of Biology, Queen's University, Kingston, ON, Canada K7L 3N6.
    Search for more papers by this author
  • Troy Day,

    1. Department of Biology, Queen's University, Kingston, ON, Canada K7L 3N6.
    2. Department of Mathematics and Statistics, Jeffery Hall, Queen's University, Kingston, ON, Canada K7L 3N6.
    Search for more papers by this author
  • Andrew F. Read

    1. Center for Infectious Disease Dynamics, Departments of Biology and Entomology, Pennsylvania State University, University Park, PA 16802, USA.
    Search for more papers by this author

  • Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.

*E-mail 4nlm@queensu.ca; Tel. (+1) 613  533 6000 ext. 75134; Fax (+1) 613 533 6617.

Summary

Almost 20 years after the development of models of malaria pathogenesis began, we are beyond the ‘proof-of-concept’ phase and these models are no longer abstract mathematical exercises. They have refined our knowledge of within-host processes, and have brought insights that could not easily have been obtained from experimentation alone. There is much potential that remains to be realized, however, both in terms of informing the design of interventions and health policy, and in terms of addressing lingering questions about the basic biology of malaria. Recent research has begun to iterate theory and data in a much more comprehensive way, and the use of statistical techniques for model fitting and comparison offers a promising approach for providing a quantitative understanding of the pathogenesis of such a complex disease.

Ancillary