Show simple item record

dc.contributor.authorDemers, Jeffery
dc.contributor.authorBewick, Sharon
dc.contributor.authorAgusto, Folashade
dc.contributor.authorCaillouët, Kevin A.
dc.contributor.authorFagan, William F.
dc.contributor.authorRobertson, Suzanne L.
dc.date.accessioned2020-11-10T15:30:09Z
dc.date.available2020-11-10T15:30:09Z
dc.date.issued2020-08-21
dc.identifier.citationDemers, J., Bewick, S., Agusto, F., Caillouët, K. A., Fagan, W. F., & Robertson, S. L. (2020). Managing disease outbreaks: The importance of vector mobility and spatially heterogeneous control. PLoS computational biology, 16(8), e1008136. https://doi.org/10.1371/journal.pcbi.1008136en_US
dc.identifier.urihttp://hdl.handle.net/1808/30815
dc.descriptionThis work is licensed under a Creative Commons Attribution 4.0 International License.en_US
dc.description.abstractManagement strategies for control of vector-borne diseases, for example Zika or dengue, include using larvicide and/or adulticide, either through large-scale application by truck or plane or through door-to-door efforts that require obtaining permission to access private property and spray yards. The efficacy of the latter strategy is highly dependent on the compliance of local residents. Here we develop a model for vector-borne disease transmission between mosquitoes and humans in a neighborhood setting, considering a network of houses connected via nearest-neighbor mosquito movement. We incorporate large-scale application of adulticide via aerial spraying through a uniform increase in vector death rates in all sites, and door-to-door application of larval source reduction and adulticide through a decrease in vector emergence rates and an increase in vector death rates in compliant sites only, where control efficacies are directly connected to real-world experimentally measurable control parameters, application frequencies, and control costs. To develop mechanistic insight into the influence of vector motion and compliance clustering on disease controllability, we determine the basic reproduction number R0 for the system, provide analytic results for the extreme cases of no mosquito movement, infinite hopping rates, and utilize degenerate perturbation theory for the case of slow but non-zero hopping rates. We then determine the application frequencies required for each strategy (alone and combined) in order to reduce R0 to unity, along with the associated costs. Cost-optimal strategies are found to depend strongly on mosquito hopping rates, levels of door-to-door compliance, and spatial clustering of compliant houses, and can include aerial spray alone, door-to-door treatment alone, or a combination of both. The optimization scheme developed here provides a flexible tool for disease management planners which translates modeling results into actionable control advice adaptable to system-specific details.en_US
dc.description.sponsorshipSimons Foundation (426126)en_US
dc.description.sponsorshipUniversity of Kansas General Research Grant (2301-2105075)en_US
dc.description.sponsorshipDepartment of Defense SERDP contract (W912HQ-16-C-0054)en_US
dc.publisherPublic Library of Scienceen_US
dc.rights© 2020 Demers et al.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.titleManaging disease outbreaks: The importance of vector mobility and spatially heterogeneous controlen_US
dc.typeArticleen_US
kusw.kuauthorAgusto, Folashade
kusw.kudepartmentEcology and Evolutionary Biologyen_US
dc.identifier.doi10.1371/journal.pcbi.1008136en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-8019-4153en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-9749-1007en_US
dc.identifier.orcidhttps://orcid.org/0000-0003-2551-0712en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.identifier.pmidPMC7480881en_US
dc.rights.accessrightsopenAccessen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

© 2020 Demers et al.
Except where otherwise noted, this item's license is described as: © 2020 Demers et al.