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

Wu, Sean L.; Sánchez C., Héctor M.; Henry, John M.; Citron, Daniel T.; Zhang, Qian; Compton, Kelly; Liang, Biyonka; Verma, Amit; Cummings, Derek A.T.; Le Menach, Arnaud; Scott, Thomas W.; Wilson, Anne L.; Lindsay, Steven W.; Moyes, Catherine L.; Hancock, Penny A.; Russell, Tanya L.; Burkot, Thomas R.; Marshall, John M.; Kiware, Samson; Reiner, Robert C.; Smith, David L.

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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 L. Wilson

Catherine L. Moyes

Penny A. Hancock

Tanya L. Russell

Thomas R. Burkot

John M. Marshall

Samson Kiware

Robert C. Reiner

David L. Smith


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.


Wu, S. L., Sánchez C., H. M., Henry, J. M., Citron, D. T., Zhang, Q., Compton, K., …Smith, D. L. (2020). Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology. PLoS Computational Biology, 16(4), Article e1007446.

Journal Article Type Article
Acceptance Date Mar 21, 2020
Online Publication Date Aug 22, 2020
Publication Date 2020
Deposit Date May 27, 2020
Publicly Available Date May 27, 2020
Journal PLoS Computational Biology
Print ISSN 1553-734X
Publisher Public Library of Science
Peer Reviewed Peer Reviewed
Volume 16
Issue 4
Article Number e1007446


Published Journal Article (3.1 Mb)

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Copyright Statement
Copyright: © 2020 Wu et al. This is an open access<br /> article distributed under the terms of the Creative<br /> Commons Attribution License, which permits<br /> unrestricted use, distribution, and reproduction in<br /> any medium, provided the original author and<br /> source are credited.

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