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A dengue model with a dynamic Aedes albopictus vector population

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  • Erickson, Richard A.
  • Presley, Steven M.
  • Allen, Linda J.S.
  • Long, Kevin R.
  • Cox, Stephen B.

Abstract

Dengue is the most commonly transmitted arthropod-borne virus in the world with 50–100 million cases annually. Within the United States, dengue is a reemerging infectious disease of concern and near the U.S.–Mexico border, up to 75% of the population of some Texas communities have had exposure to dengue. Understanding dengue disease dynamics is critical to predicting and understanding the disease. These dynamics depend upon diverse factors such as socioeconomic conditions, the local environment, and vector biology. Here, we study dengue by examining the role of temperature in driving vector dynamics. To do this, we created a Susceptible, Exposed, Infectious, Recovered host and Susceptible, Exposed, Infectious vector (SEIR/SEI) model. The SEIR/SEI model was then used in conjunction with an Aedes albopictus population model to create a vector-based disease model. The vector-based diseased model was then forced by temperature.

Suggested Citation

  • Erickson, Richard A. & Presley, Steven M. & Allen, Linda J.S. & Long, Kevin R. & Cox, Stephen B., 2010. "A dengue model with a dynamic Aedes albopictus vector population," Ecological Modelling, Elsevier, vol. 221(24), pages 2899-2908.
    • Handle: RePEc:eee:ecomod:v:221:y:2010:i:24:p:2899-2908
    DOI: 10.1016/j.ecolmodel.2010.08.036
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    References listed on IDEAS

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    1. Derek A.T. Cummings & Rafael A. Irizarry & Norden E. Huang & Timothy P. Endy & Ananda Nisalak & Kumnuan Ungchusak & Donald S. Burke, 2004. "Travelling waves in the occurrence of dengue haemorrhagic fever in Thailand," Nature, Nature, vol. 427(6972), pages 344-347, January.
    2. Erickson, Richard A. & Presley, Steven M. & Allen, Linda J.S. & Long, Kevin R. & Cox, Stephen B., 2010. "A stage-structured, Aedes albopictus population model," Ecological Modelling, Elsevier, vol. 221(9), pages 1273-1282.
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    Citations

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    Cited by:

    1. Tiago França Melo De Lima & Raquel Martins Lana & Tiago Garcia De Senna Carneiro & Cláudia Torres Codeço & Gabriel Souza Machado & Lucas Saraiva Ferreira & Líliam César De Castro Medeiros & Clodoveu A, 2016. "DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics," IJERPH, MDPI, vol. 13(9), pages 1-21, September.
    2. Josef Zapletal & Madhav Erraguntla & Zach N Adelman & Kevin M Myles & Mark A Lawley, 2018. "Impacts of diurnal temperature and larval density on aquatic development of Aedes aegypti," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-16, March.
    3. Josef Zapletal & Himanshu Gupta & Madhav Erraguntla & Zach N Adelman & Kevin M Myles & Mark A Lawley, 2019. "Predicting aquatic development and mortality rates of Aedes aegypti," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-8, May.
    4. Jeon-Young Kang & Jared Aldstadt, 2017. "The Influence of Spatial Configuration of Residential Area and Vector Populations on Dengue Incidence Patterns in an Individual-Level Transmission Model," IJERPH, MDPI, vol. 14(7), pages 1-14, July.
    5. Haocheng Wu & Chen Wu & Qinbao Lu & Zheyuan Ding & Ming Xue & Junfen Lin, 2019. "Evaluating the effects of control interventions and estimating the inapparent infections for dengue outbreak in Hangzhou, China," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-16, August.

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