期刊名称：Journal of Advanced Veterinary and Animal Research
印刷版ISSN：2311-7710
出版年度：2019
卷号：6
期号：2
页码：148-157
DOI：10.5455/javar.2019.f325
出版社：Bangladesh Agricultural University, Faculty of Veterinary Science
摘要：Objective: The objective of this study was to assess the risk of rabies entry through the movement of hunting dog from Garut District to Sumatera Island with a semi-quantitative approach. Materials and Methods: Rabies entry assessment used the standard risk analysis according to the World Organization for Animal Health, with a semi-quantitative approach referring to Australian Biosecurity. Risk estimation calculation used Microsoft Excel and probabilities were estimated using Monte Carlo stochastic simulation modeling with @Risk (Palisade Corporation). Results: Risk estimation were considered as “very low” with a 0.02 (90%; 0.01–0.03) probability. The probability of undetected rabies-infected dog during Veterinary Certificate issuance [node probability (NP4)] was considered as the highest, with “moderate” likelihood and 0.63 (90%; 0.51–0.75) of probability value. The number of dog movement to Sumatera reached 27,000 heads per year which 5,050 heads of them come from Garut District. There were 2 of 100 dogs from Garut District entered to Sumatera possibly infected by rabies. The five highest parameters most determinant of the risk were dog vaccination before transported (0.66), dog obtained from other District (0.41), vaccination program (0.32), serologically test (0.27), and history of vaccination (0.23). Conclusion: Risk estimation from assessing on rabies entry to Sumatera through hunting dogs movement from Garut District was considered “very low.” Risk mitigation is focused on the highest parameters that contribute the most to risk based on the results of the sensitivity analysis. Semi-quantitative likelihood evaluations can consider the volume of dog traffic which is an important issue in risk analysis which is not easy to get with a simpler qualitative approach. J. Adv. Vet. Anim. Res., 6(2): 148-157, June 2019
