Modeling the Dynamics of Dengue Fever

  • Kun Hu
  • Christian Thoens
  • Simone Bianco
  • Stefan Edlund
  • Matthew Davis
  • Judith Douglas
  • James Kaufman
Conference paper

DOI: 10.1007/978-3-642-37210-0_53

Volume 7812 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Hu K. et al. (2013) Modeling the Dynamics of Dengue Fever. In: Greenberg A.M., Kennedy W.G., Bos N.D. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2013. Lecture Notes in Computer Science, vol 7812. Springer, Berlin, Heidelberg

Abstract

Dengue is a major international public health concern that impacts one-third of the world’s population. There are four serotypes of the dengue virus (DENV). Infection with one serotype affords life-long immunity to that serotype but only temporary cross immunity (CI) to other serotypes. The risk of lethal complications is elevated upon re-infection, possibly because of the effect of antibody-dependent enhancement (ADE). In this paper we propose a system dynamics model that captures both host and vector populations, latency, and four dengue serotypes. This model allows one to study both CI and ADE. Modeling the Aedes vector adds complexity, but we consider this to be important because combating the mosquito vector may be the most practical intervention in the absence of an effective vaccine. Our results support the need to model the vector population and ADE to explain the observed epidemiological data.

Keywords

Dengue cross immunity antibody-dependent enhancement system dynamics model dynamic behaviors 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kun Hu
    • 1
  • Christian Thoens
    • 2
  • Simone Bianco
    • 3
  • Stefan Edlund
    • 1
  • Matthew Davis
    • 1
  • Judith Douglas
    • 1
  • James Kaufman
    • 1
  1. 1.IBM Almaden Research CenterSan JoseUSA
  2. 2.Federal Institute for Risk Assessment, Biological SafetyBerlinGermany
  3. 3.Bioengineering and Therapeutic SciencesUniversity of California, San FranciscoSan FranciscoUSA