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西尼罗河病毒和东部马脑炎病毒高概率栖息地识别,用于选择佛罗里达州哨兵鸡监测点。

West Nile Virus and Eastern Equine Encephalitis Virus High Probability Habitat Identification for the Selection of Sentinel Chicken Surveillance Sites in Florida.

出版信息

J Am Mosq Control Assoc. 2022 Mar 1;38(1):1-6. doi: 10.2987/21-7049.

DOI:10.2987/21-7049
PMID:35276726
Abstract

To mitigate the effects of West Nile virus (WNV) and eastern equine encephalitis virus (EEEV), the state of Florida conducts a serosurveillance program that uses sentinel chickens operated by mosquito control programs at numerous locations throughout the state. Coop locations were initially established to detect St. Louis encephalitis virus (SLEV), and coop placement was determined based on the location of human SLEV infections that occurred between 1959 and 1977. Since the introduction of WNV into Florida in 2001, WNV has surpassed SLEV as the primary arbovirus in Florida. Identifying high probability locations for WNV and EEEV transmission and relocating coops to areas of higher arbovirus activity would improve the sensitivity of the sentinel chicken surveillance program. Using 2 existing models, this study conducted an overlay analysis to identify areas with high probability habitats for both WNV and EEEV activity. This analysis identified approximately 7,800 km2 (about 4.5% of the state) as high probability habitat for supporting both WNV and EEEV transmission. Mosquito control programs can use the map resulting from this analysis to improve their sentinel chicken surveillance programs, increase the probability of virus detection, reduce operational costs, and allow for a faster, targeted response to virus detection.

摘要

为了减轻西尼罗河病毒(WNV)和东部马脑炎病毒(EEEV)的影响,佛罗里达州开展了一项血清监测计划,该计划利用蚊虫控制项目在全州众多地点运营的哨兵鸡。鸡舍的位置最初是为了检测圣路易斯脑炎病毒(SLEV)而设立的,鸡舍的位置是根据 1959 年至 1977 年期间发生的人类 SLEV 感染的位置来确定的。自 2001 年 WNV 传入佛罗里达州以来,WNV 已超过 SLEV 成为佛罗里达州的主要虫媒病毒。确定 WNV 和 EEEV 传播的高概率地点,并将鸡舍搬迁到虫媒病毒活动较高的地区,将提高哨兵鸡监测计划的敏感性。本研究使用现有的两个模型进行了叠加分析,以确定WNV 和 EEEV 活动高概率栖息地的区域。该分析确定了约 7800 平方公里(约占该州的 4.5%)为支持 WNV 和 EEEV 传播的高概率栖息地。蚊虫控制项目可以使用该分析生成的地图来改进其哨兵鸡监测计划,提高病毒检测的概率,降低运营成本,并允许对病毒检测做出更快、更有针对性的反应。

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