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.

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.

Citation

Wu, S. L., Sánchez C., H. M., Henry, J. M., Citron, D. T., Zhang, Q., Compton, K., Liang, B., Verma, A., Cummings, D. A., Le Menach, A., Scott, T. W., Wilson, A. L., Lindsay, S. W., Moyes, C. L., Hancock, P. A., Russell, T. L., Burkot, T. R., Marshall, J. M., Kiware, S., Reiner, R. C., & Smith, D. L. (2020). Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology. PLoS Computational Biology, 16(4), Article e1007446. https://doi.org/10.1371/journal.pcbi.1007446

• 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
• DOI: https://doi.org/10.1371/journal.pcbi.1007446
• Public URL: https://durham-repository.worktribe.com/output/1269888