Sampling for global epidemic models and the topology of an international airport network.
Sampling for global epidemic models and the topology of an international airport network.
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DOI：
10.1371/journal.pone.0003154
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发表时间：
2008-09-08
期刊：
影响因子：
3.7
通讯作者：
Goedecke DM
中科院分区：
文献类型：
--
作者：
Bobashev G;Morris RJ;Goedecke DM
描述流感、严重急性呼吸系统综合症 (SARS) 和结核病 (TB) 等传染病全球传播的数学模型通常将国际机场样本视为支持疾病传播的网络。然而，对于应该选择多少个城市以及如何选择这些城市尚未达成共识。利用2000年商业航空公司向官方航空公司指南（OAG）报告的机场航班数据，我们检查了在不同选择规则下获得的网络样本的网络特征。此外，我们还根据最大的航班量和最大的城市人口检查了不同规模的样本。我们的研究表明，尽管网络特征的偏差随着样本量的减少而增加，但包括最大的机场、最大的城市、联系最紧密的城市和最中心的城市在内的相对较少的区域足以描述流感全球传播的动态。分析表明，相对较少的城市（近 3000 个城市中的大约 200 或 300 个）可以捕获足够的网络信息来充分描述流感等疾病的全球传播情况。小机场之间的交通流量较弱可能会产生噪音，并掩盖地面交通等其他传播方式。
Mathematical models that describe the global spread of infectious diseases such as influenza, severe acute respiratory syndrome (SARS), and tuberculosis (TB) often consider a sample of international airports as a network supporting disease spread. However, there is no consensus on how many cities should be selected or on how to select those cities. Using airport flight data that commercial airlines reported to the Official Airline Guide (OAG) in 2000, we have examined the network characteristics of network samples obtained under different selection rules. In addition, we have examined different size samples based on largest flight volume and largest metropolitan populations. We have shown that although the bias in network characteristics increases with the reduction of the sample size, a relatively small number of areas that includes the largest airports, the largest cities, the most-connected cities, and the most central cities is enough to describe the dynamics of the global spread of influenza. The analysis suggests that a relatively small number of cities (around 200 or 300 out of almost 3000) can capture enough network information to adequately describe the global spread of a disease such as influenza. Weak traffic flows between small airports can contribute to noise and mask other means of spread such as the ground transportation.
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DOI：
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发表时间：
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DOI：
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发表时间：
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