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A Spatial Model of Mosquito Host-Seeking Behavior

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  • Bree Cummins
  • Ricardo Cortez
  • Ivo M Foppa
  • Justin Walbeck
  • James M Hyman

Abstract

Mosquito host-seeking behavior and heterogeneity in host distribution are important factors in predicting the transmission dynamics of mosquito-borne infections such as dengue fever, malaria, chikungunya, and West Nile virus. We develop and analyze a new mathematical model to describe the effect of spatial heterogeneity on the contact rate between mosquito vectors and hosts. The model includes odor plumes generated by spatially distributed hosts, wind velocity, and mosquito behavior based on both the prevailing wind and the odor plume. On a spatial scale of meters and a time scale of minutes, we compare the effectiveness of different plume-finding and plume-tracking strategies that mosquitoes could use to locate a host. The results show that two different models of chemotaxis are capable of producing comparable results given appropriate parameter choices and that host finding is optimized by a strategy of flying across the wind until the odor plume is intercepted. We also assess the impact of changing the level of host aggregation on mosquito host-finding success near the end of the host-seeking flight. When clusters of hosts are more tightly associated on smaller patches, the odor plume is narrower and the biting rate per host is decreased. For two host groups of unequal number but equal spatial density, the biting rate per host is lower in the group with more individuals, indicative of an attack abatement effect of host aggregation. We discuss how this approach could assist parameter choices in compartmental models that do not explicitly model the spatial arrangement of individuals and how the model could address larger spatial scales and other probability models for mosquito behavior, such as Lévy distributions. Author Summary: Mosquito-borne diseases can spread when a mosquito bites a vertebrate host to obtain a blood meal for egg-laying. The first step in the transmission process consists of the mosquitoes seeking and finding a host. Mosquitoes use the wind direction and odors, such as carbon dioxide, emitted by the hosts in order to locate a host to bite. We present a spatial computational model of the host-seeking process in a region where hosts are heterogeneously distributed in clusters. The model is used to analyze the success in finding hosts once the mosquitoes are close to the host. We show that the number of mosquito-host contacts increases as hosts become more widely spaced within their clusters; that mosquito flight perpendicular to the wind leads to greater success in locating a host; and that the number of bites per host decreases when hosts aggregate into larger clusters.

Suggested Citation

  • Bree Cummins & Ricardo Cortez & Ivo M Foppa & Justin Walbeck & James M Hyman, 2012. "A Spatial Model of Mosquito Host-Seeking Behavior," PLOS Computational Biology, Public Library of Science, vol. 8(5), pages 1-13, May.
  • Handle: RePEc:plo:pcbi00:1002500
    DOI: 10.1371/journal.pcbi.1002500
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    References listed on IDEAS

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    1. D. L. Smith & J. Dushoff & R. W. Snow & S. I. Hay, 2005. "The entomological inoculation rate and Plasmodium falciparum infection in African children," Nature, Nature, vol. 438(7067), pages 492-495, November.
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    1. Anguelov, Roumen & Dufourd, Claire & Dumont, Yves, 2017. "Simulations and parameter estimation of a trap-insect model using a finite element approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 133(C), pages 47-75.
    2. T Alex Perkins & Thomas W Scott & Arnaud Le Menach & David L Smith, 2013. "Heterogeneity, Mixing, and the Spatial Scales of Mosquito-Borne Pathogen Transmission," PLOS Computational Biology, Public Library of Science, vol. 9(12), pages 1-16, December.
    3. Maneerat, Somsakun & Daudé, Eric, 2016. "A spatial agent-based simulation model of the dengue vector Aedes aegypti to explore its population dynamics in urban areas," Ecological Modelling, Elsevier, vol. 333(C), pages 66-78.
    4. Virgillito, Chiara & Manica, Mattia & Marini, Giovanni & Caputo, Beniamino & Torre, Alessandra della & Rosà, Roberto, 2021. "Modelling arthropod active dispersal using Partial differential equations: the case of the mosquito Aedes albopictus," Ecological Modelling, Elsevier, vol. 456(C).
    5. Hiroko Mori & Joshua Wu & Motomu Ibaraki & Franklin W. Schwartz, 2018. "Key Factors Influencing the Incidence of West Nile Virus in Burleigh County, North Dakota," IJERPH, MDPI, vol. 15(9), pages 1-19, September.

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