Phytopathology. 2004 Feb;94(2):209-15. doi: 10.1094/PHYTO.2004.94.2.209.
ABSTRACT Rhizomania disease of sugar beet represents a major economic threat to the sugar industry in the United Kingdom. Here we use the UK rhizomania epidemic as an exemplar of a range of highly infectious spatially heterogeneous diseases. Using a spatially explicit stochastic model, we investigated the efficacy of a spectrum of possible control strategies, both locally reactive and national in character. These include the use of novel cultivars of beet with different responses to infection, changes in cultivation practice, and reactive containment policies at the farm scale. We show that strictly local responses, including a containment policy similar to that initially implemented in the United Kingdom in response to the disease, are largely ineffective in slowing the spread because they fail to match the natural scale of the epidemic. Larger spatial-scale processes are considerably more successful. We conclude that epidemics have intrinsic temporal and spatial scales that must be matched by any control strategy if it is to be both effective and efficient. We have generated probability distributions for the proportion of farms symptomatic. Over the course of the epidemic, such distributions develop a bimodality that we hypothesize to correspond to the matching of spatial heterogeneity in the susceptible population to the intrinsic scales of the epidemic.
摘要 甜菜丛根病是英国制糖业的主要经济威胁。在这里，我们以英国的丛根病流行作为一系列具有高度传染性的空间异质性疾病的范例。我们使用空间显式随机模型，研究了一系列可能的控制策略的效果，包括具有不同感染反应的新型甜菜品种的使用、耕作方式的改变，以及在农场规模上采取的反应性遏制政策。我们表明，严格的局部反应，包括类似于英国最初针对该疾病实施的遏制政策，在减缓传播方面基本上是无效的，因为它们无法与疫情的自然规模相匹配。更大的空间尺度过程则更为成功。我们的结论是，疫情具有内在的时间和空间尺度，如果控制策略要有效和高效，就必须与之相匹配。我们已经生成了农场出现症状的比例的概率分布。在疫情期间，这种分布呈现双峰性，我们假设这与易感性人群中的空间异质性与疫情的内在尺度相匹配相对应。
