Predictive qualitative risk model of bovine rabies occurrence in Brazil
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- 作者：Guilherme Basseto Braga ; Jos茅 Henrique Hildebr ; Grisi-Filho ; Bruno Meireles Leite ; Elaine F谩tima de Sena ; Ricardo Augusto Dias
- 关键词：Rabies ; Bats ; Risk ; Model ; Brazil ; Bovine
- 刊名：Preventive Veterinary Medicine
- 出版年：1 March, 2014
- 年：2014
- 卷：113
- 期：4
- 页码：536-546
- 全文大小：4251 K
文摘
Bovine rabies remains endemic in Brazil and despite control efforts, the disease still spreads insidiously. The main vector is the hematophagous bat, Desmodus rotundus. The present work aimed to create a predictive qualitative model of the occurrence of bovine rabies in each municipality in 25 of the 27 Brazilian States. The risk of rabies transmission from bats to bovine was estimated using decision-tree models of receptivity and vulnerability. Questionnaires, which covered a number of questions related to the surveillance of possible risk factors, such as bovine rabies outbreaks in the previous year, the presence of bat roosts, bat rabies positivity and environmental changes, were sent to the local veterinary units of each State. The bovine density and geomorphologic features were obtained from national databases and geographic information systems. Of the 433 municipalities presenting bovine rabies outbreaks in 2010, 178 (41.1%) were classified by the model as high risk, 212 (49.0%) were classified as moderate risk, 25 (5.8%) were classified as low risk, whereas the risk was undetermined in 18 municipalities (4.1%). An ROC curve was built to determine if the risk evaluated by the model could adequately discriminate between municipalities with and without rabies occurrence in future years. The risk estimator for the year 2011 was classified as moderately accurate. In the future, these models could allow the targeting of rabies control efforts, with the adoption of control measures directed to the higher risk locations and the optimization of the field veterinary staff deployment throughout the country. Additionally, efforts must be made to encourage continuous surveillance of risk factors.