Farrahi Katayoun, Emonet Rémi, Cebrian Manuel
Department of Computing, Goldsmiths, University of London, London, United Kingdom.
Department of Machine Learning, Laboratoire Hubert Curien, Saint-Etienne, France.
PLoS One. 2014 May 1;9(5):e95133. doi: 10.1371/journal.pone.0095133. eCollection 2014.
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.
传统的接触者追踪依赖于对传染病传播所涉及的人际身体互动网络的了解。然而,由于隐私限制和数据同化存在噪声,这个网络通常很难准确重建。已知通过手机获得的通信记录是身体互动网络的良好替代指标,它们可能为接触者追踪提供有价值的工具。基于这一假设,我们提出了一种接触者追踪模型,其中感染在人际身体网络中传播,而这个网络永远无法完全恢复;接触者追踪则在作为前者替代指标的通信网络中进行。我们将这个双重模型应用于一个涵盖72名学生、为期9个月的数据集上,该数据集同时包含身体互动以及移动通信记录。我们的结果表明,广泛的接触者追踪策略可能会显著降低疫情的最终规模,主要是通过影响其发病高峰来实现。然而,我们发现,对于面对面互动网络和通信互动网络之间重叠度较低的情况,由于随着疫情发展成本迅速增加,接触者追踪仅在疫情爆发初期有效。总体而言,通过移动通信记录进行接触者追踪可能是遏制传染病爆发的一个可行选择。