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Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia

机译:使用有限的剔除方法来控制野生动物的疾病暴发:对澳大利亚野猪的经典猪瘟入侵进行建模

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摘要

Disease modelling is one approach for providing new insights into wildlife disease epidemiology. This paper describes a spatio-temporal, stochastic, susceptible- exposed-infected-recovered process model that simulates the potential spread of classical swine fever through a documented, large and free living wild pig population following a simulated incursion. The study area (300 000 km2) was in northern Australia. Published data on wild pig ecology from Australia, and international Classical Swine Fever data was used to parameterise the model. Sensitivity analyses revealed that herd density (best estimate 1-3 pigs km-2), daily herd movement distances (best estimate approximately 1 km), probability of infection transmission between herds (best estimate 0.75) and disease related herd mortality (best estimate 42%) were highly influential on epidemic size but that extraordinary movements of pigs and the yearly home range size of a pig herd were not. CSF generally established (98% of simulations) following a single point introduction. CSF spread at approximately 9 km2 per day with low incidence rates (< 2 herds per day) in an epidemic wave along contiguous habitat for several years, before dying out (when the epidemic arrived at the end of a contiguous sub-population or at a low density wild pig area). The low incidence rate indicates that surveillance for wildlife disease epidemics caused by short lived infections will be most efficient when surveillance is based on detection and investigation of clinical events, although this may not always be practical. Epidemics could be contained and eradicated with culling (aerial shooting) or vaccination when these were adequately implemented. It was apparent that the spatial structure, ecology and behaviour of wild populations must be accounted for during disease management in wildlife. An important finding was that it may only be necessary to cull or vaccinate relatively small proportions of a population to successfully contain and eradicate some wildlife disease epidemics.
机译:疾病建模是一种提供有关野生动物疾病流行病学的新见解的方法。本文描述了一个时空,随机,易感暴露-感染-恢复的过程模型,该模型模拟了模拟入侵后经典猪瘟在有记录的大型自由生活野猪种群中的传播潜力。研究区域(300 000 km 2 )位于澳大利亚北部。来自澳大利亚的有关野生猪生态学的公开数据以及国际经典猪瘟数据用于参数化该模型。敏感性分析表明,牛群密度(最佳估计1-3头猪公里 -2 ),每日牛群移动距离(最佳估计约1公里),感染在猪群之间传播的概率(最佳估计0.75)和疾病相关的畜群死亡率(最佳估计为42%)对疫情规模有很大的影响,但猪的异常活动和猪群的年家庭规模却没有。在单点介绍之后,通常建立了CSF(模拟的98%)。 CSF每天以大约9 km 2 的速度传播,沿邻近的栖息地在流行病波中以低发病率(每天<2个畜群/天)传播数年,直到死亡为止(当流行病到来时)。连续的亚种群或低密度的野猪区域)。较低的发病率表明,当监测是基于对临床事件的检测和调查时,由短期感染引起的野生动植物疾病流行的监测将是最有效的,尽管这可能并不总是可行的。当流行病得到适当实施时,可以通过扑杀(空中射击)或疫苗进行控制和根除。显然,在野生动植物的疾病管理过程中必须考虑野生种群的空间结构,生态和行为。一个重要的发现是,只需要对相对较小比例的人群进行剔除或接种疫苗就可以成功地遏制和根除某些野生动植物疾病的流行病。

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