Karsten S, Rave G, Krieter J
Institute of Animal Breeding and Husbandry, Christian-Albrechts-University, Hermann-Rodewald-Street 6, 24118 Kiel, Germany.
Vet Microbiol. 2005 Jul 1;108(3-4):199-205. doi: 10.1016/j.vetmic.2005.04.008.
A stochastic and spatial simulation model was developed to simulate the spread of classical swine fever virus among herds in a certain area. A model is a simplification of a real system. The mechanisms and parameters are often not exactly known. Validation is necessary to gain insight into model behaviour and to identify risk factors with great impact on the response variables. Several risk factors such as incubation period, number of daily farm contacts, probability of detection, probability of infection after contact, probability of local spread and time from infection to infectivity were considered in the model as probability distributions in order to take the stochastic component of disease dynamics into account. In order to estimate the effects of the risk factors on the response variables mean size and duration of epidemics, a sensitivity analysis was performed. A fractional factorial design with two-level factors (2(7-2) design) was developed to gain the maximum strength with minimum demand on the calculating capacity. The main factors were unconfounded with any other main factor and also unconfounded with two-factor interactions. Apart from the time from infection to infectivity, all risk factors had a significant effect on the mean size and duration of epidemics (p<0.05). Eight two-factor interactions had a significant influence as well (p<0.05). Mainly, two-factor interactions with probability of detection were significant thus emphasising the impact of a rapid detection of outbreaks. The reaction of the simulation responses to changing of the parameter values was consistent with the expected reaction.
开发了一个随机空间模拟模型,以模拟经典猪瘟病毒在某一地区猪群间的传播。模型是对真实系统的简化。其机制和参数往往并不确切知晓。为深入了解模型行为并识别对响应变量有重大影响的风险因素,进行验证很有必要。模型中考虑了几个风险因素,如潜伏期、每日农场接触数量、检测概率、接触后感染概率、局部传播概率以及从感染到具有传染性的时间,将其作为概率分布,以便考虑疾病动态的随机成分。为估计风险因素对响应变量(疫情的平均规模和持续时间)的影响,进行了敏感性分析。开发了一种具有两级因子的部分因子设计(2(7 - 2)设计),以在对计算能力需求最小的情况下获得最大强度。主要因子与任何其他主要因子均无混杂,且与双因子交互作用也无混杂。除了从感染到具有传染性的时间外,所有风险因素对疫情的平均规模和持续时间均有显著影响(p<0.05)。八个双因子交互作用也有显著影响(p<0.05)。主要是与检测概率的双因子交互作用显著,从而突出了快速检测疫情的影响。模拟响应随参数值变化的反应与预期反应一致。