Temporal Analysis and Spatial Modeling of the Distribution and Abundance of Cs. melanura, Eastern Equine Encephalitis Vector: Connecticut, 1997-2012
Author
White, ChelsiIssue Date
2016Keywords
Culiseta melanuraEastern Equine Encephalitis (EEE)
Spatial Modeling
Temporal Analysis
Vector-borne Disease
Epidemiology
Connecticut
Advisor
Brown, Heidi
Metadata
Show full item recordPublisher
The University of Arizona.Rights
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.Abstract
Eastern Equine Encephalitis virus is a vector-borne virus amplified by the Culiseta melanura mosquito in an enzootic avian cycle, causing high morbidity and mortality to horses and humans when contracted as incidental hosts. The virus is distributed across most of the eastern United States, Canada, and Gulf coast, and has been expanding in geographic range and season of activity over time. Spatial-temporal trends in Cs. melanura abundance were correlated with available meteorological (temperature and precipitation) and remotely sensed environmental data for the period of 1997-2012 in Connecticut. The effects of inter-annual changes in precipitation, temperature, and groundwater levels on Cs. melanura abundances using time-series linear regression and cross-correlation analyses were inconclusive. Habitat modeling using logistic regression and landscape-based predictive variables demonstrated strong efficiency (46.2%) and acceptable sensitivity and specificity (65.6 and 78.6%, respectively) using NDVI difference and distance from palustrine areas as predictive factors. Remotely sensed data can improve the understanding of vector abundance patterns, helping to forecast future outbreaks and regional expansions by guiding surveillance efforts.Type
textElectronic Thesis
Degree Name
M.S.Degree Level
mastersDegree Program
Graduate CollegeEpidemiology