Spatial epidemiology of eastern equine encephalitis in Florida

<p>Abstract</p> <p>Background</p> <p>Eastern Equine Encephalitis virus (EEEV) is an alphavirus with high pathogenicity in both humans and horses. Florida continues to have the highest occurrence of human cases in the USA, with four fatalities recorded in 2010. Unlike ot...

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Main Authors: Vander Kelen Patrick T, Downs Joni A, Stark Lillian M, Loraamm Rebecca W, Anderson James H, Unnasch Thomas R
Format: Article
Language:English
Published: BMC 2012-11-01
Series:International Journal of Health Geographics
Subjects:
Online Access:http://www.ij-healthgeographics.com/content/11/1/47
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author Vander Kelen Patrick T
Downs Joni A
Stark Lillian M
Loraamm Rebecca W
Anderson James H
Unnasch Thomas R
author_facet Vander Kelen Patrick T
Downs Joni A
Stark Lillian M
Loraamm Rebecca W
Anderson James H
Unnasch Thomas R
author_sort Vander Kelen Patrick T
collection DOAJ
description <p>Abstract</p> <p>Background</p> <p>Eastern Equine Encephalitis virus (EEEV) is an alphavirus with high pathogenicity in both humans and horses. Florida continues to have the highest occurrence of human cases in the USA, with four fatalities recorded in 2010. Unlike other states, Florida supports year-round EEEV transmission. This research uses GIS to examine spatial patterns of documented horse cases during 2005–2010 in order to understand the relationships between habitat and transmission intensity of EEEV in Florida.</p> <p>Methods</p> <p>Cumulative incidence rates of EEE in horses were calculated for each county. Two cluster analyses were performed using density-based spatial clustering of applications with noise (DBSCAN). The first analysis was based on regional clustering while the second focused on local clustering. Ecological associations of EEEV were examined using compositional analysis and Euclidean distance analysis to determine if the proportion or proximity of certain habitats played a role in transmission.</p> <p>Results</p> <p>The DBSCAN algorithm identified five distinct regional spatial clusters that contained 360 of the 438 horse cases. The local clustering resulted in 18 separate clusters containing 105 of the 438 cases. Both the compositional analysis and Euclidean distance analysis indicated that the top five habitats positively associated with horse cases were rural residential areas, crop and pastureland, upland hardwood forests, vegetated non-forested wetlands, and tree plantations.</p> <p>Conclusions</p> <p>This study demonstrates that in Florida tree plantations are a focus for epizootic transmission of EEEV. It appears both the abundance and proximity of tree plantations are factors associated with increased risk of EEE in horses and therefore humans. This association helps to explain why there is are spatially distinct differences in the amount of EEE horse cases across Florida.</p>
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spelling doaj.art-3cb328ec007b4394b1c2770a94a4988e2022-12-22T00:09:03ZengBMCInternational Journal of Health Geographics1476-072X2012-11-011114710.1186/1476-072X-11-47Spatial epidemiology of eastern equine encephalitis in FloridaVander Kelen Patrick TDowns Joni AStark Lillian MLoraamm Rebecca WAnderson James HUnnasch Thomas R<p>Abstract</p> <p>Background</p> <p>Eastern Equine Encephalitis virus (EEEV) is an alphavirus with high pathogenicity in both humans and horses. Florida continues to have the highest occurrence of human cases in the USA, with four fatalities recorded in 2010. Unlike other states, Florida supports year-round EEEV transmission. This research uses GIS to examine spatial patterns of documented horse cases during 2005–2010 in order to understand the relationships between habitat and transmission intensity of EEEV in Florida.</p> <p>Methods</p> <p>Cumulative incidence rates of EEE in horses were calculated for each county. Two cluster analyses were performed using density-based spatial clustering of applications with noise (DBSCAN). The first analysis was based on regional clustering while the second focused on local clustering. Ecological associations of EEEV were examined using compositional analysis and Euclidean distance analysis to determine if the proportion or proximity of certain habitats played a role in transmission.</p> <p>Results</p> <p>The DBSCAN algorithm identified five distinct regional spatial clusters that contained 360 of the 438 horse cases. The local clustering resulted in 18 separate clusters containing 105 of the 438 cases. Both the compositional analysis and Euclidean distance analysis indicated that the top five habitats positively associated with horse cases were rural residential areas, crop and pastureland, upland hardwood forests, vegetated non-forested wetlands, and tree plantations.</p> <p>Conclusions</p> <p>This study demonstrates that in Florida tree plantations are a focus for epizootic transmission of EEEV. It appears both the abundance and proximity of tree plantations are factors associated with increased risk of EEE in horses and therefore humans. This association helps to explain why there is are spatially distinct differences in the amount of EEE horse cases across Florida.</p>http://www.ij-healthgeographics.com/content/11/1/47Eastern equine encephalitisGISSpatial epidemiologyCompositional analysisEuclidean distance
spellingShingle Vander Kelen Patrick T
Downs Joni A
Stark Lillian M
Loraamm Rebecca W
Anderson James H
Unnasch Thomas R
Spatial epidemiology of eastern equine encephalitis in Florida
International Journal of Health Geographics
Eastern equine encephalitis
GIS
Spatial epidemiology
Compositional analysis
Euclidean distance
title Spatial epidemiology of eastern equine encephalitis in Florida
title_full Spatial epidemiology of eastern equine encephalitis in Florida
title_fullStr Spatial epidemiology of eastern equine encephalitis in Florida
title_full_unstemmed Spatial epidemiology of eastern equine encephalitis in Florida
title_short Spatial epidemiology of eastern equine encephalitis in Florida
title_sort spatial epidemiology of eastern equine encephalitis in florida
topic Eastern equine encephalitis
GIS
Spatial epidemiology
Compositional analysis
Euclidean distance
url http://www.ij-healthgeographics.com/content/11/1/47
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