Search

Abstract: A GIS-based risk index model was developed to quantify EEEV transmission risk to horses in the State of Florida. EEEV is a highly pathogenic arbovirus that is endemic along the east coast of the United States, and it is generally fatal to both horses and humans. The model evaluates EEEV transmission risk at individual raster cells in map on a continuous scale of 0–1. The risk index is derived based on local habitat features and the composition and configuration of surrounding land cover types associated with EEEV transmission. The model was verified and validated using the locations of documented horse cases of EEEV. These results of the verification and validation indicate that the model is able to predict locations of EEEV transmission to horses broadly across the state. The model is relatively robust to regional variation in EEEV transmission and habitat conditions in Florida, and it accurately predicted nearly all verification and validation cases in the Panhandle, North, and Central regions of the state. The model performed less accurately in the South, where relatively few cases are documented. Despite these differences, the model provides a useful way to assess EEEV risk both from a regional perspective and at more localized scales. The resulting predictive maps are designed to guide EEEV surveillance and prevention efforts by county mosquito control districts. [Copyright &y& Elsevier]

Background: 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. Methods: 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. Results: 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. Conclusions: 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. [ABSTRACT FROM AUTHOR]