Gubbins Simon
Centre for Epidemiology and Risk Analysis, Veterinary Laboratories Agency, New Haw, Addlestone, Surrey KT15 3NB, UK.
Prev Vet Med. 2005 Feb;67(2-3):143-56. doi: 10.1016/j.prevetmed.2004.08.007.
My aim was to develop a stochastic, spatial model describing the spread of scrapie between sheep flocks in Great Britain; I wanted a model, which could subsequently be used to assess the efficacy of different control strategies. The structure of the model reflects the demography of the British sheep flock, including a description of the contact structure between flocks. The dynamics of scrapie were incorporated through two probabilities associated with each flock: of acquiring infection and of experiencing a within-flock outbreak following exposure. The acquisition of infection depends on whether or not a flock buys-in sheep and, if it does, whether or not it trades with an affected flock. Once a flock is exposed, the probability of a within-flock outbreak occurring and its duration depend on the basic reproductive number, the prion-protein (PrP) genotype profile and the flock size. The model was validated using regional data from two postal surveys conducted in 1998 and 2002, which demonstrated that the model captures the spatial dynamics of scrapie (at least at a regional level). Moreover, the predicted distribution for the duration of a within-flock outbreak reflects the duration of outbreaks reported in the literature. Using the model to predict long-term trends in the proportion of affected flocks suggested that, even without control measures beyond the removal of animals with clinical signs, scrapie ultimately will disappear from the national flock, though it is likely to be decades before the disease is eliminated. However, there were scenarios consistent with the available data which suggested that scrapie could remain endemic within the British sheep flock. Consequently, it is essential to take this uncertainty in the long-term dynamics of scrapie into account when considering the efficacy of control strategies. Although control strategies were not explicitly examined, the model suggests two aspects important for control: larger flocks remain affected for longer and provide infection for other, smaller flocks and animal movements must be traceable.
我的目标是建立一个随机空间模型,描述英国羊群中羊瘙痒病的传播情况;我需要一个模型,随后可用于评估不同控制策略的效果。该模型的结构反映了英国羊群的种群统计学特征,包括羊群间接触结构的描述。羊瘙痒病的动态变化通过与每个羊群相关的两个概率纳入模型:感染的概率以及接触后羊群内爆发疫情的概率。感染的获得取决于一个羊群是否购入羊只,如果购入,是否与受感染的羊群进行交易。一旦一个羊群受到感染,羊群内爆发疫情的概率及其持续时间取决于基本繁殖数、朊病毒蛋白(PrP)基因型分布以及羊群规模。该模型使用1998年和2002年进行的两次邮政调查的区域数据进行了验证,结果表明该模型捕捉到了羊瘙痒病的空间动态(至少在区域层面)。此外,预测的羊群内疫情持续时间分布反映了文献中报道的疫情持续时间。使用该模型预测受感染羊群比例的长期趋势表明,即使不采取除清除有临床症状动物之外的控制措施,羊瘙痒病最终也会从全国羊群中消失,不过该病可能需要数十年才能消除。然而,存在与现有数据一致的情况表明,羊瘙痒病可能会在英国羊群中保持地方流行。因此,在考虑控制策略的效果时,必须考虑到羊瘙痒病长期动态中的这种不确定性。虽然没有明确研究控制策略,但该模型表明了控制的两个重要方面:较大的羊群受影响的时间更长,并会感染其他较小的羊群,而且动物的移动必须可追踪。