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The Influence of Spatial Configuration of Residential Area and Vector Populations on Dengue Incidence Patterns in an Individual-Level Transmission Model

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  • Jeon-Young Kang

    (Department of Geography, University at Buffalo, Buffalo, NY 14261, USA)

  • Jared Aldstadt

    (Department of Geography, University at Buffalo, Buffalo, NY 14261, USA)

Abstract

Dengue is a mosquito-borne infectious disease that is endemic in tropical and subtropical countries. Many individual-level simulation models have been developed to test hypotheses about dengue virus transmission. Often these efforts assume that human host and mosquito vector populations are randomly or uniformly distributed in the environment. Although, the movement of mosquitoes is affected by spatial configuration of buildings and mosquito populations are highly clustered in key buildings, little research has focused on the influence of the local built environment in dengue transmission models. We developed an agent-based model of dengue transmission in a village setting to test the importance of using realistic environments in individual-level models of dengue transmission. The results from one-way ANOVA analysis of simulations indicated that the differences between scenarios in terms of infection rates as well as serotype-specific dominance are statistically significant. Specifically, the infection rates in scenarios of a realistic environment are more variable than those of a synthetic spatial configuration. With respect to dengue serotype-specific cases, we found that a single dengue serotype is more often dominant in realistic environments than in synthetic environments. An agent-based approach allows a fine-scaled analysis of simulated dengue incidence patterns. The results provide a better understanding of the influence of spatial heterogeneity on dengue transmission at a local scale.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:7:p:792-:d:104794
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    1. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
    2. 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.
    3. Bernard Cazelles & Mario Chavez & Anthony J McMichael & Simon Hales, 2005. "Nonstationary Influence of El Niño on the Synchronous Dengue Epidemics in Thailand," PLOS Medicine, Public Library of Science, vol. 2(4), pages 1-1, April.
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    1. Luba Pascoe & Thomas Clemen & Karen Bradshaw & Devotha Nyambo, 2022. "Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models," IJERPH, MDPI, vol. 19(23), pages 1-24, November.

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