Highly dynamic animal contact network and implications on disease transmission.
Highly dynamic animal contact network and implications on disease transmission.
复制标题
DOI：
10.1038/srep04472
复制
发表时间：
2014-03-26
影响因子：
4.6
通讯作者：
Lanzas C
中科院分区：
文献类型：
--
作者：
Chen S;White BJ;Sanderson MW;Amrine DE;Ilany A;Lanzas C
宿主之间的接触模式被认为是导致病原体不均匀传播的最关键因素之一。因此，网络在传染病建模中得到了广泛的应用。然而，由于缺乏准确的观测和合适的分析工具，大多数研究假设网络结构是静态的。在这项研究中，我们使用高时间和空间分辨率的动物位置数据，构建一个高分辨率的接触网络相关的传染病传播。聚集在每小时一级的动物接触网络是高度可变的和动态的内和之间的天，网络结构（网络度分布）和网络中的度分布（度顺序）的个人排名。我们将网络度分布和度序异质性与常用的基于接触的直接传播疾病模型相结合，量化了这两个异质性来源对传染病动力学的影响。基于这两种不均匀性的组合，模拟了四种情况。模拟结果表明，疾病的动力学和个人贡献的新感染在这四个条件下，两个参数设置有很大的不同。对于基本繁殖数较小（即R0 < 2）的病原体，接触网络的变化对疾病动态的影响更大。
Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R0 < 2).
登录
查看更多内容
影响因子：
4.6
作者：
Campbell, Ellsworth;Salathe, Marcel
通讯作者：
Salathe, Marcel
影响因子：
3.8
作者：
Ciccolini, M.;Dahl, J.;Woolhouse, M. E. J.
通讯作者：
Woolhouse, M. E. J.
影响因子：
1.4
作者：
Eames, K. T. D.
通讯作者：
Eames, K. T. D.
影响因子：
3.9
作者：
Parham, Paul E.;Ferguson, Neil M.
通讯作者：
Ferguson, Neil M.
影响因子：
3.7
作者：
Isella L;Romano M;Barrat A;Cattuto C;Colizza V;Van den Broeck W;Gesualdo F;Pandolfi E;Ravà L;Rizzo C;Tozzi AE
通讯作者：
Tozzi AE