Efficient detection of contagious outbreaks in massive metropolitan encounter networks.
Efficient detection of contagious outbreaks in massive metropolitan encounter networks.
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DOI：
10.1038/srep05099
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发表时间：
2014-06-06
影响因子：
4.6
通讯作者：
Cebrian M
中科院分区：
文献类型：
--
作者：
Sun L;Axhausen KW;Lee DH;Cebrian M
在大城市网络中，身体接触仍然难以追踪，尽管这是传染病爆发传播的关键途径。在日常交通使用过程中的共存接触为我们提供了一个城市规模的时间分辨的物理接触网络，由300万交通用户中的10亿个接触组成。在这里，我们研究的优势，这种共存结构的知识可以提供早期检测的传染性爆发。我们首先研究的“朋友传感器”计划-一个简单的，但通用的策略，只需要本地信息-并证明它提供了显着的模拟疫情的早期检测。利用完整的网络结构，然后，我们确定先进的“全球传感器集”，获得大量的预警时间节省的朋友传感器计划。具有最高遭遇次数的个体是最有效的传感器，其性能与具有最高旅行频率、探索行为和结构中心性的个体相当。当测试对传感器尺寸的依赖性和评估传感器的可靠性时，出现了效率平衡;我们发现，通过仅监测最高程度的0.01%的人口，可以实现大量和可靠的交货期。
Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the “friend sensor” scheme - a simple, but universal strategy requiring only local information - and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced “global sensor sets”, obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree.
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DOI：
10.1073/pnas.0906910106
发表时间：
2009-12-22
影响因子：
11.1
作者：
Balcan, Duygu;Colizza, Vittoria;Vespignani, Alessandro
通讯作者：
Vespignani, Alessandro
DOI：
10.1073/pnas.1006219107
发表时间：
2010-12-14
影响因子：
11.1
作者：
Chan, Emily H.;Brewer, Timothy F.;Brownstein, John S.
通讯作者：
Brownstein, John S.
影响因子：
4.4
作者：
FELD, SL
通讯作者：
FELD, SL
影响因子：
64.8
作者：
Bond, Robert M.;Fariss, Christopher J.;Jones, Jason J.;Kramer, Adamd. I.;Marlow, Cameron;Settle, Jaime E.;Fowler, James H.
通讯作者：
Fowler, James H.
影响因子：
158.5
作者：
Christakis, Nicholas A.;Fowler, James H.
通讯作者：
Fowler, James H.