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The number of links to and from the starting node as a predictor of epidemic size in small-size directed networks

机译:在小型定向网络中,作为起始流行病预测指标的往返于起始节点的链接数

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摘要

Much recent modelling is focusing on epidemics in large-scale complex networks. Whether or not findings of these investigations also apply to networks of small size is still an open question. This is an important gap for many biological applications, including the spread of the oomycete pathogen Phytophthora ramorum in networks of plant nurseries. We use numerical simulations of disease spread and establishment in directed networks of 100 individual nodes at four levels of connectivity. Factors governing epidemic spread are network structure (local, small-world, random, scale-free) and the probabilities of infection persistence in a node and of infection transmission between connected nodes. Epidemic final size at equilibrium varies widely depending on the starting node of infection, although the latter does not affect the threshold condition for spread. The number of links from (out-degree) but not the number of links to (in-degree) the starting node of the epidemic explains a substantial amount of variation in final epidemic size at equilibrium irrespective of the structure of the network. The proportion of variance in epidemic size explained by the out-degree of the starting node increases with the level of connectivity. Targeting highly connected nodes is thus likely to make disease control more effective also in case of small-size populations, a result of relevance not just for the horticultural trade, but for epidemiology in general.
机译:最近的建模主要集中在大规模复杂网络中的流行病。这些调查的结果是否也适用于小型网络仍然是一个悬而未决的问题。这是许多生物学应用的重要缺口,包括卵菌病原体疫霉菌在植物苗圃网络中的传播。我们在四个连接级别的100个单独节点的定向网络中使用疾病传播和建立的数值模拟。控制流行病传播的因素是网络结构(本地,小世界,随机,无规模)以及节点中感染持久性和连接节点之间感染传播的可能性。尽管感染并不会影响传播的临界条件,但最终流行时的最终规模在很大程度上取决于感染的起始节点。从流行程度的(向外)链接数量到到达流行程度的(in程度链接)数量,而不是网络的结构,说明了在平衡状态下最终流行病规模的大量变化。流行程度的方差比例由起始节点的向外程度解释,随连接级别的增加而增加。因此,针对人口众多的节点,即使在人口较少的情况下,也有可能使疾病控制更加有效,这不仅与园艺贸易有关,而且与总体流行病学有关。

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