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一种用于预测东部马脑炎病毒在佛罗里达州向马匹传播的风险指数模型。

A risk index model for predicting eastern equine encephalitis virus transmission to horses in Florida.

作者信息

Kelen Patrick Vander, Downs Joni A, Unnasch Thomas, Stark Lillian

机构信息

Department of Global Health, University of South Florida, 4202 E Fowler Ave, Tampa, FL 33620.

School of Geosciences, University of South Florida, 4202 E Fowler Ave, Tampa, FL 33620.

出版信息

Appl Geogr. 2014 Mar 1;48:79-86. doi: 10.1016/j.apgeog.2014.01.012.

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 to 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.

摘要

开发了一种基于地理信息系统(GIS)的风险指数模型,以量化佛罗里达州马匹感染东部马脑炎病毒(EEEV)的传播风险。EEEV是一种高致病性虫媒病毒,在美国东海岸流行,通常对马匹和人类都具有致命性。该模型在地图上以0到1的连续尺度评估各个栅格单元的EEEV传播风险。风险指数是根据当地栖息地特征以及与EEEV传播相关的周边土地覆盖类型的组成和配置得出的。利用记录在案的马匹感染EEEV病例的位置对该模型进行了验证。验证结果表明,该模型能够大致预测全州范围内EEEV向马匹传播的位置。该模型对佛罗里达州EEEV传播和栖息地条件的区域差异具有相对较强的鲁棒性,并且准确地预测了该州狭长地带、北部和中部地区几乎所有的验证和确认病例。该模型在南部的预测准确性较低,那里记录的病例相对较少。尽管存在这些差异,但该模型提供了一种从区域角度和更局部尺度评估EEEV风险的有用方法。生成的预测地图旨在指导各县蚊虫控制区的EEEV监测和预防工作。

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