A comparison of spatial-based targeted disease mitigation strategies using mobile phone data
A comparison of spatial-based targeted disease mitigation strategies using mobile phone data
复制标题
使用手机数据的基于空间的有针对性的疾病缓解策略的比较
DOI：
10.1140/epjds/s13688-018-0145-9
复制
发表时间：
2018
期刊：
影响因子：
3.6
通讯作者：
Mirco Musolesi
中科院分区：
文献类型：
--
作者：
S. Rubrichi;Z. Smoreda;Mirco Musolesi
疫情爆发是一项重大的医疗保健挑战，尤其是在发展中国家，疫情是导致死亡的主要原因之一。能够迅速针对亚人群进行监测和控制的方法对于在疫情期间加强防控和缓解进程至关重要。利用来自科特迪瓦的一个真实数据集，这项工作试图揭示疾病传播动态的社会地理异质性。通过采用一个基于手机通话详单记录（CDRs）的空间显式集合种群传染病模型，我们研究了流动模式的差异如何影响一种假设的传染病爆发的过程。我们考虑了现有的关于人类流动和互动的空间维度的不同测量方法，并分析了它们在识别风险最高的亚人群（作为隔离对策的最佳候选对象）方面的相关性。本文提出的方法进一步证明，手机数据可以被有效利用，以促进我们对个人空间行为及其与传染病传染风险之间关系的理解。特别是，我们表明，基于CDRs的个人空间活动和互动指标有望深入了解传染异质性，从而制定缓解策略，为国家层面的疫情期间的决策提供支持。
Epidemic outbreaks are an important healthcare challenge, especially in developing countries where they represent one of the major causes of mortality. Approaches that can rapidly target subpopulations for surveillance and control are critical for enhancing containment and mitigation processes during epidemics. Using a real-world dataset from Ivory Coast, this work presents an attempt to unveil the socio-geographical heterogeneity of disease transmission dynamics. By employing a spatially explicit meta-population epidemic model derived from mobile phone Call Detail Records (CDRs), we investigate how the differences in mobility patterns may affect the course of a hypothetical infectious disease outbreak. We consider different existing measures of the spatial dimension of human mobility and interactions, and we analyse their relevance in identifying the highest risk sub-population of individuals, as the best candidates for isolation countermeasures. The approaches presented in this paper provide further evidence that mobile phone data can be effectively exploited to facilitate our understanding of individuals’ spatial behaviour and its relationship with the risk of infectious diseases’ contagion. In particular, we show that CDRs-based indicators of individuals’ spatial activities and interactions hold promise for gaining insight of contagion heterogeneity and thus for developing mitigation strategies to support decision-making during country-level epidemics.