Document Type
Article
Publication Date
2020
Keywords
Arbovirus, Eastern Equine Encephalitis, ecological modelling, Florida, Maxent, spatial epidemiology
Digital Object Identifier (DOI)
https://doi.org/10.1080/19475683.2020.1730962
Abstract
Eastern Equine Encephalitis virus (EEEV) is a virus found predominantly east of the Mississippi River in the United States that can be fatal to both equines and humans. The disease has previously been most prolific in states like Florida, but there has been an increase in the prevalence in other states further up north on the east coast of the United States in recent years. The purpose of this research is to use the ecological niche modelling program Maxent to model EEEV habitat suitability probability. This research utilized data of fatality incidence in equine hosts, versus sentinel chicken infection data, the spatial data traditionally utilized for mapping EEEV. This research produced a map of habitat suitability, which expanded on previous risk models by utilizing additional environmental factors. It confirmed areas of higher probability identified by previous models but identified more narrow areas of higher probability as well. This model adds to the literature applying ecological modelling techniques to spatial epidemiology. It highlights spaces that represent the culmination of environmental factors for the transmission of EEEV. Considering these environmental factors identified can assist in identifying places where there is a higher risk of EEEV as new cases begin to appear.
Rights Information
This work is licensed under a Creative Commons Attribution 4.0 License.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Annals of GIS, v. 26, issue 2, p. 133-147
Scholar Commons Citation
Burch, Claire; Loraamm, Rebecca; Unnasch, Thomas R.; and Downs, Joni A., "Utilizing Ecological Niche Modelling to Predict Habitat Suitability of Eastern Equine Encephalitis in Florida" (2020). School of Geosciences Faculty and Staff Publications. 2239.
https://digitalcommons.usf.edu/geo_facpub/2239