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巴塞罗那犬类中犬恶丝虫的流行情况:地理空间预测模型的验证

Prevalence of Dirofilaria immitis in dogs from Barcelona: Validation of a geospatial prediction model.

作者信息

Montoya-Alonso José Alberto, Carretón Elena, Simón Luis, González-Miguel Javier, García-Guasch Laín, Morchón Rodrigo, Simón Fernando

机构信息

Internal Medicine, Faculty of Veterinary Medicine, University Institute for Biomedical and Health Research (IUIBS), University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain.

Internal Medicine, Faculty of Veterinary Medicine, University Institute for Biomedical and Health Research (IUIBS), University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain.

出版信息

Vet Parasitol. 2015 Sep 15;212(3-4):456-9. doi: 10.1016/j.vetpar.2015.06.025. Epub 2015 Jul 2.

Abstract

Like other vector borne infections, the distribution of dirofilariosis caused by Dirofilaria immitis is influenced by climatic factors, which regulate the diversity and abundance of mosquito species able to transmit the parasite. Geographical Information Systems (GIS) can predict the distribution and epidemiological behavior of dirofilariosis based on temperature and humidity data. This study analyses the prevalence and current distribution of canine dirofilariosis in the province of Barcelona (Northeastern Spain), and uses a GIS model to evaluate the relationship between the spatial distribution of positive cases and different geo-environmental factors. Canine dirofilariosis is present in all the studied regions but unevenly distributed. The general prevalence is 2.4%, being located most of positive dogs in areas where the model predict both high number of annual generations of D. immitis in vectors and humidity, as a consequence of the presence of irrigated crops or the proximity to the sea. Furthermore, in the urban area of Barcelona, infected dogs were located in districts surrounded or close to parks and green areas. The model can be used as a tool to determine the need of implementation of prophylactic protocols in pets living in municipalities from these regions, based on the geo-environmental characteristics of the area.

摘要

与其他媒介传播的感染一样,由犬恶丝虫引起的恶丝虫病的分布受气候因素影响,气候因素调节着能够传播该寄生虫的蚊种的多样性和丰度。地理信息系统(GIS)可以根据温度和湿度数据预测恶丝虫病的分布和流行病学行为。本研究分析了巴塞罗那省(西班牙东北部)犬恶丝虫病的患病率和当前分布情况,并使用GIS模型评估阳性病例的空间分布与不同地理环境因素之间的关系。犬恶丝虫病在所有研究区域均有存在,但分布不均。总体患病率为2.4%,大多数阳性犬位于模型预测媒介中犬恶丝虫年世代数多且湿度高的地区,这是由于存在灌溉作物或靠近大海所致。此外,在巴塞罗那市区,感染犬位于被公园和绿地环绕或靠近公园和绿地的区域。该模型可作为一种工具,根据这些地区的地理环境特征,确定在这些地区城市中生活的宠物实施预防方案的必要性。

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