Open AccessModelling distributions of Aedes aegypti and Aedes albopictus using climate, host density and interspecies competition
Author(s) -
Bingyi Yang,
Brooke A. Borgert,
Barry W. Alto,
Carl K. Boohene,
J.S. Brew,
Kelly Deutsch,
James DeValerio,
Rhoel R. Dinglasan,
Daniel Dixon,
Joseph M. Faella,
Sandra L. Fisher-Grainger,
Gregory E. Glass,
Reginald Hayes,
David F. Hoel,
Austin Horton,
Agne Janusauskaite,
Bill Kellner,
Moritz U. G. Kraemer,
Keira J. Lucas,
Johana Medina,
Rachel Morreale,
William D. Petrie,
Robert C. Reiner,
Michael T. Riles,
Henrik Salje,
David L. Smith,
John P. Smith,
Amy Solis,
Jason Stuck,
Chalmers Vasquez,
Katie F. Williams,
RuiDe Xue,
Derek A. T. Cummings
Publication year - 2021
Publication title -
plos neglected tropical diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.99
H-Index - 135
eISSN - 1935-2735
pISSN - 1935-2727
DOI - 10.1371/journal.pntd.0009063
Subject(s) - aedes albopictus , aedes aegypti , negative binomial distribution , aedes , biology , abundance (ecology) , vector (molecular biology) , host (biology) , ecology , statistics , larva , mathematics , poisson distribution , biochemistry , gene , recombinant dna
Florida faces the challenge of repeated introduction and autochthonous transmission of arboviruses transmitted by Aedes aegypti and Aedes albopictus . Empirically-based predictive models of the spatial distribution of these species would aid surveillance and vector control efforts. To predict the occurrence and abundance of these species, we fit a mixed-effects zero-inflated negative binomial regression to a mosquito surveillance dataset with records from more than 200,000 trap days, representative of 53% of the land area and ranging from 2004 to 2018 in Florida. We found an asymmetrical competitive interaction between adult populations of Aedes aegypti and Aedes albopictus for the sampled sites. Wind speed was negatively associated with the occurrence and abundance of both vectors. Our model predictions show high accuracy (72.9% to 94.5%) in validation tests leaving out a random 10% subset of sites and data since 2017, suggesting a potential for predicting the distribution of the two Aedes vectors.