Epidemic contact tracing via communication traces.
Epidemic contact tracing via communication traces.
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DOI：
10.1371/journal.pone.0095133
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Cebrian M
中科院分区：
文献类型：
--
作者：
Farrahi K;Emonet R;Cebrian M
传统的接触者追踪依赖于对身体相互作用的人际网络的了解，传染病的爆发是在人际网络中传播的。然而，由于隐私限制和噪声数据同化，该网络通常难以准确重建。由移动的电话获得的通信轨迹被认为是物理交互网络的良好代理，并且它们可以为联系人跟踪提供有价值的工具。基于这一假设，我们提出了一个接触追踪模型，其中感染在物理人际网络中传播，永远无法完全恢复;接触追踪发生在作为第一个代理的通信网络中。我们应用这个双模型的数据集，涵盖72名学生在9个月的时间内，其中的物理交互以及移动的通信痕迹是已知的。我们的研究结果表明，广泛的接触者追踪策略可能会显着减少最终规模的流行病，主要是影响其发病率的高峰。然而，我们发现，对于面对面和通信交互网络之间的低重叠，接触者追踪仅在疫情爆发初期有效，这是由于随着疫情的发展，成本迅速增加。总的来说，通过移动的电话通信追踪接触者可能是阻止传染病爆发的可行选择。
Traditional contact tracing relies on knowledge of the interpersonal network of physical interactions, where contagious outbreaks propagate. However, due to privacy constraints and noisy data assimilation, this network is generally difficult to reconstruct accurately. Communication traces obtained by mobile phones are known to be good proxies for the physical interaction network, and they may provide a valuable tool for contact tracing. Motivated by this assumption, we propose a model for contact tracing, where an infection is spreading in the physical interpersonal network, which can never be fully recovered; and contact tracing is occurring in a communication network which acts as a proxy for the first. We apply this dual model to a dataset covering 72 students over a 9 month period, for which both the physical interactions as well as the mobile communication traces are known. Our results suggest that a wide range of contact tracing strategies may significantly reduce the final size of the epidemic, by mainly affecting its peak of incidence. However, we find that for low overlap between the face-to-face and communication interaction network, contact tracing is only efficient at the beginning of the outbreak, due to rapidly increasing costs as the epidemic evolves. Overall, contact tracing via mobile phone communication traces may be a viable option to arrest contagious outbreaks.
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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
影响因子：
9.3
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Stehlé J;Voirin N;Barrat A;Cattuto C;Colizza V;Isella L;Régis C;Pinton JF;Khanafer N;Van den Broeck W;Vanhems P
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Vanhems P
DOI：
10.1073/pnas.1006155107
发表时间：
2010-12-28
影响因子：
11.1
作者：
Crandall, David J.;Backstrom, Lars;Kleinberg, Jon
通讯作者：
Kleinberg, Jon
DOI：
10.1073/pnas.1009094108
发表时间：
2010-12-21
影响因子：
11.1
作者：
Salathe, Marcel;Kazandjieva, Maria;Jones, James H.
通讯作者：
Jones, James H.
影响因子：
4.3
作者：
Salathé M;Jones JH
通讯作者：
Jones JH