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Stochastic spatio-temporal modelling of African swine fever spread in the European Union during the high risk period

机译:高危时期在欧洲联盟传播的非洲猪瘟的随机时空模型

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African swine fever (ASF) is a notifiable viral pig disease with high mortality and serious socio-economic consequences. Since ASF emerged in Georgia in 2007 the disease has spread to several neighbouring countries and cases have been detected in areas bordering the European Union (EU). It is uncertain how fast the virus would be able to spread within the unrestricted European trading area if it were introduced into the EU. This project therefore aimed to develop a model for the spread of ASF within and between the 27 Member States (MS) of the EU during the high risk period (HRP) and to identify MS during that period would most likely contribute to ASF spread ("super-spreaders") or MS that would most likely receive cases from other MS ("super-receivers"). A stochastic spatio-temporal state-transition model using simulated individual farm records was developed to assess silent ASF virus spread during different predefined HRPs of 10-60 days duration. Infection was seeded into farms of different pig production types in each of the 27 MS. Direct pig-to-pig transmission and indirect transmission routes (pig transport lorries and professional contacts) were considered the main pathways during the early stages of an epidemic. The model was parameterised using data collated from EUROSTAT, TRACES, a questionnaire sent to MS, and the scientific literature. Model outputs showed that virus circulation was generally limited to 1-2 infected premises per outbreak (95% IQR: 1-4; maximum: 10) with large breeder farms as index case resulting in most infected premises. Seven MS caused between-MS spread due to intra-Community trade during the first 10 days after seeding infection. For a HRP of 60 days from virus introduction, movements of infected pigs will originate at least once from 16 MS, with 6 MS spreading ASF in more than 10% of iterations. Two thirds of all intra-Community spread was linked to six trade links only. Denmark, the Netherlands, Lithuania and Latvia were identified as "super-spreaders"; Germany and Poland as "super-receivers". In the sensitivity analysis, the total number of premises per country involved in intra-Community trade was found to be a key determinant for the between-MS spread dynamic and needs to be further investigated. It was concluded that spread during the HRP is likely to be limited, especially if the HRP is short. This emphasises the importance of having good disease awareness in all MS for early disease detection
机译:非洲猪瘟(ASF)是一种应报告的病毒猪疾病,具有高死亡率和严重的社会经济后果。自2007年ASF在佐治亚州出现以来,该病已蔓延到几个邻国,并在与欧盟(EU)接壤的地区发现了病例。如果将病毒引入欧盟,目前尚不确定该病毒能在不受限制的欧洲贸易区内传播的速度。因此,该项目旨在开发一种模型,用于在高风险期(HRP)期间在欧盟27个成员国(MS)内及其之间传播ASF,并确定该时期内的MS最有可能促进ASF的传播(“超级传播者”)或最有可能从其他MS(“超级接收者”)接收案件的MS。建立了使用模拟个体农场记录的随机时空状态转换模型,以评估在10-60天持续时间的不同预定义HRP期间无声ASF病毒的传播。在27个MS中,感染被播种到不同猪生产类型的农场。在疫情的早期阶段,直接的猪到猪的传播和间接的传播途径(运输猪的卡车和专业人士)被认为是主要途径。使用从EUROSTAT,TRACES,发送给MS的调查表和科学文献中收集的数据对模型进行参数化。模型输出显示,每次爆发通常将病毒传播限制在1-2个受感染场所(95%IQR:1-4;最大:10),而大型繁殖场则是导致大多数受感染场所的指标。在种子感染后的前10天内,由于社区内部贸易,有7位MS引起MS间传播。在病毒引入后的60天的HRP中,受感染猪的移动至少要从16 MS开始一次,其中6 MS会在10%以上的迭代中传播ASF。所有社区内部价差的三分之二仅与六个贸易联系有关。丹麦,荷兰,立陶宛和拉脱维亚被确定为“超级传播者”;德国和波兰为“超级接收者”。在敏感性分析中,发现每个国家/地区参与社区内部贸易的场所总数是MS间传播动态的关键决定因素,需要进一步调查。结论是,HRP期间的传播可能会受到限制,尤其是在HRP较短的情况下。这强调了对所有MS进行早期疾病检测的良好疾病意识的重要性

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