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利用2018 - 2022年美国的温度和降水数据评估马腺疫疫情趋势

Evaluating Trends in Strangles Outbreaks Using Temperature and Precipitation Data in the United States of America for 2018-2022.

作者信息

Thomas Bryce A, Saylor Ryan K, Taylor Zachary P, Rhodes DeLacy V L

机构信息

Department of Biology, Berry College, Mount Berry, GA 30149, USA.

Department of Environmental Science and Studies, Berry College, Mount Berry, GA 30149, USA.

出版信息

Pathogens. 2023 Aug 29;12(9):1106. doi: 10.3390/pathogens12091106.

Abstract

Strangles is a highly contagious upper respiratory infection of equids that is globally distributed. The causative agent of strangles, subspecies , can be spread through indirect contact with infected fomites, and studies have shown this microbe to live well in varying environmental conditions. The purpose of this study was to analyze strangles case numbers across the United States of America from 2018 to 2022 to investigate potential temporal or weather patterns associated with outbreaks. Diagnosed case records were obtained from the Equine Disease Communication Center, university databases, government agencies, or veterinary diagnostic labs, and geographic information systems (GISs) were used to map cases and to acquire relevant meteorological data from outbreak areas. These data were analyzed using logistic regression to explore trends that occur between outbreaks and changes in temperature and precipitation. Initial review of weather data suggested monthly changes in strangles case numbers corresponded with changing seasons. Logistic regression indicated that changes in monthly average temperature and minimum temperature were significantly associated with increased or decreased odds of strangles outbreaks, respectively. Future analyses should focus on weather data isolated within a smaller region or state to better resolve trends in strangles outbreaks throughout the continental USA.

摘要

马腺疫是一种在全球范围内传播的、高度传染性的马属动物上呼吸道感染疾病。马腺疫的病原体——亚种,可以通过与受感染的污染物间接接触传播,并且研究表明这种微生物能在不同的环境条件下良好存活。本研究的目的是分析2018年至2022年美国各地的马腺疫病例数量,以调查与疫情爆发相关的潜在时间或天气模式。从马病通讯中心、大学数据库、政府机构或兽医诊断实验室获取确诊病例记录,并使用地理信息系统(GIS)绘制病例地图,并从疫情爆发地区获取相关气象数据。使用逻辑回归分析这些数据,以探索疫情爆发与温度和降水变化之间出现的趋势。对天气数据的初步审查表明,马腺疫病例数量的月度变化与季节变化相对应。逻辑回归表明,月平均温度和最低温度的变化分别与马腺疫爆发几率的增加或减少显著相关。未来的分析应集中在较小区域或州内的天气数据上,以便更好地解析美国大陆马腺疫疫情爆发的趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9c3/10535521/c0c24e1e50d9/pathogens-12-01106-g001.jpg

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