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Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology

  • Sean L. Wu
  • , Héctor M. Sánchez C
  • , John M. Henry
  • , Daniel T. Citron
  • , Qian Zhang
  • , Kelly Compton
  • , Biyonka Liang
  • , Amit Verma
  • , Derek A.T. Cummings
  • , Arnaud Le Menach
  • , Thomas W. Scott
  • , Anne Wilson
  • , Steven W. Lindsay
  • , Catherine L. Moyes
  • , Penny A. Hancock
  • , Tanya L. Russell
  • , Thomas R. Burkot
  • , John M. Marshall
  • , Samson Kiware
  • , Robert C. Reiner
  • David L. Smith
  • University of California at Berkeley
  • Instituto Tecnologico de Estudios Superiores de Monterrey
  • University of Washington
  • Emory University
  • University of Florida
  • Clinton Health Access Initiative, Inc.
  • University of California at Davis
  • Durham University
  • University of Oxford
  • James Cook University Queensland
  • Ifakara Health Institute

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)

Abstract

Mosquitoes are important vectors for pathogens that infect humans and other vertebrate animals. Some aspects of adult mosquito behavior and mosquito ecology play an important role in determining the capacity of vector populations to transmit pathogens. Here, we reexamine factors affecting the transmission of pathogens by mosquitoes using a new approach. Unlike most previous models, this framework considers the behavioral states and state transitions of adult mosquitoes through a sequence of activity bouts. We developed a new framework for individual-based simulation models called MBITES (Mosquito Boutbased and Individual-based Transmission Ecology Simulator). In MBITES, it is possible to build models that simulate the behavior and ecology of adult mosquitoes in exquisite detail on complex resource landscapes generated by spatial point processes. We also developed an ordinary differential equation model which is the Kolmogorov forward equations for models developed in MBITES under a specific set of simplifying assumptions. While mosquito infection and pathogen development are one possible part of a mosquito’s state, that is not our main focus. Using extensive simulation using some models developed in MBITES, we show that vectorial capacity can be understood as an emergent property of simple behavioral algorithms interacting with complex resource landscapes, and that relative density or sparsity of resources and the need to search can have profound consequences for mosquito populations’ capacity to transmit pathogens.

Original languageEnglish
Article numbere1007446
Pages (from-to)e1007446
JournalPLoS Computational Biology
Volume16
Issue number4
DOIs
Publication statusPublished - 22 Apr 2020

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