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dc.contributor.authorCampbell, Lindsay P.
dc.contributor.authorReuman, Daniel C.
dc.contributor.authorLutomiah, Joel
dc.contributor.authorPeterson, A. Townsend
dc.contributor.authorLinthicum, Kenneth J.
dc.contributor.authorBritch, Seth C.
dc.contributor.authorAnyamba, Assaf
dc.contributor.authorSang, Rosemary
dc.date.accessioned2022-09-19T20:45:27Z
dc.date.available2022-09-19T20:45:27Z
dc.date.issued2019-12-17
dc.identifier.citationCampbell LP, Reuman DC, Lutomiah J, Peterson AT, Linthicum KJ, Britch SC, et al. (2019) Predicting Abundances of Aedes mcintoshi, a primary Rift Valley fever virus mosquito vector. PLoS ONE 14(12): e0226617. https://doi.org/10.1371/journal.pone.0226617en_US
dc.identifier.urihttp://hdl.handle.net/1808/33530
dc.description.abstractRift Valley fever virus (RVFV) is a mosquito-borne zoonotic arbovirus with important livestock and human health, and economic consequences across Africa and the Arabian Peninsula. Climate and vegetation monitoring guide RVFV forecasting models and early warning systems; however, these approaches make monthly predictions and a need exists to predict primary vector abundances at finer temporal scales. In Kenya, an important primary RVFV vector is the mosquito Aedes mcintoshi. We used a zero-inflated negative binomial regression and multimodel averaging approach with georeferenced Ae. mcintoshi mosquito counts and remotely sensed climate and topographic variables to predict where and when abundances would be high in Kenya and western Somalia. The data supported a positive effect on abundance of minimum wetness index values within 500 m of a sampling site, cumulative precipitation values 0 to 14 days prior to sampling, and elevated land surface temperature values ~3 weeks prior to sampling. The probability of structural zero counts of mosquitoes increased as percentage clay in the soil decreased. Weekly retrospective predictions for unsampled locations across the study area between 1 September and 25 January from 2002 to 2016 predicted high abundances prior to RVFV outbreaks in multiple foci during the 2006–2007 epizootic, except for two districts in Kenya. Additionally, model predictions supported the possibility of high Ae. mcintoshi abundances in Somalia, independent of Kenya. Model-predicted abundances were low during the 2015–2016 period when documented outbreaks did not occur, although several surveillance systems issued warnings. Model predictions prior to the 2018 RVFV outbreak indicated elevated abundances in Wajir County, Kenya, along the border with Somalia, but RVFV activity occurred west of the focus of predicted high Ae. mcintoshi abundances.en_US
dc.publisherPublic Library of Scienceen_US
dc.rightsThis is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.en_US
dc.rights.urihttps://creativecommons.org/publicdomain/zero/1.0/en_US
dc.titlePredicting Abundances of Aedes mcintoshi, a primary Rift Valley fever virus mosquito vectoren_US
dc.typeArticleen_US
kusw.kuauthorReuman, Daniel C.
kusw.kuauthorPeterson, A. Townsend
kusw.kudepartmentEcology and Evolutionary Biologyen_US
kusw.kudepartmentKansas Biological Surveyen_US
dc.identifier.doi10.1371/journal.pone.0226617en_US
dc.identifier.orcidhttps://orcid.org/0000-0001-6069-1198en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.rights.accessrightsopenAccessen_US


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This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Except where otherwise noted, this item's license is described as: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.