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

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 re-examine 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 Bout-based 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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pcbi.1007446

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Role:
Author
ORCID:
0000-0002-5781-9493
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Role:
Author
ORCID:
0000-0001-7378-8853
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Role:
Author
ORCID:
0000-0001-8684-2003
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Author
ORCID:
0000-0002-1282-4176
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Role:
Author
ORCID:
0000-0001-7313-8594


Publisher:
Public Library of Science
Journal:
PLoS computational biology More from this journal
Volume:
16
Issue:
4
Article number:
e1007446
Publication date:
2020-04-22
Acceptance date:
2020-03-21
DOI:
EISSN:
1553-7358
ISSN:
1553-734X
Pmid:
32320389


Language:
English
Keywords:
Pubs id:
1101431
Local pid:
pubs:1101431
Deposit date:
2020-05-05

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