识别在公共交通系统中传播疾病的有传染性的旅行者（CS SI）
- 2020 年 4 月 6 日
- 筆記
最近一种新型冠状病毒的爆发及其迅速传播突出了了解人类流动性的重要性。 密闭空间，例如公共交通工具(例如巴士及火车) ，提供适当的环境让感染迅速广泛传播。因此，调查个人在公共交通系统上的行动模式和身体接触，对于了解传染病爆发的驱动因素至关重要。例如，以前的工作已经探索了人类行动固有的循环模式对疾病传播的影响，但是没有考虑其他方面，如行进的距离或遭遇的次数。 在这里，我们考虑多个流动性维度同时揭示关键信息的设计有效的干预策略。 我们使用在澳大利亚悉尼收集到的一个月的全市智能卡旅行数据，按照三个维度对公交乘客进行分类，即探险程度，旅行距离和遭遇次数。 此外，我们模拟疾病在传输网络上的传播，并追踪传染路径。 通过改变病原菌的感染概率和悬浮时间，详细调查了各分类组之间的传播情况。我们的研究结果同时描述多个维度上的个体，揭示了不同乘客群体之间复杂的感染相互作用，当只考虑单一维度时，这一点仍然是隐藏的。我们也确定了那些在特定疾病特征下比其他人更有影响力的群体。
原文题目：Identifying highly influential travellers for spreading disease on a public transport system
原文：The recent outbreak of a novel coronavirus and its rapid spread underlines the importance of understanding human mobility. Enclosed spaces, such as public transport vehicles (e.g. buses and trains), offer a suitable environment for infections to spread widely and quickly. Investigating the movement patterns and the physical encounters of individuals on public transit systems is thus critical to understand the drivers of infectious disease outbreaks. For instance previous work has explored the impact of recurring patterns inherent in human mobility on disease spread, but has not considered other dimensions such as the distance travelled or the number of encounters. Here, we consider multiple mobility dimensions simultaneously to uncover critical information for the design of effective intervention strategies. We use one month of citywide smart card travel data collected in Sydney, Australia to classify bus passengers along three dimensions, namely the degree of exploration, the distance travelled and the number of encounters. Additionally, we simulate disease spread on the transport network and trace the infection paths. We investigate in detail the transmissions between the classified groups while varying the infection probability and the suspension time of pathogens. Our results show that characterizing individuals along multiple dimensions simultaneously uncovers a complex infection interplay between the different groups of passengers, that would remain hidden when considering only a single dimension. We also identify groups that are more influential than others given specific disease characteristics,
原文作者：Ahmad El Shoghri
原文地址：https://arxiv.org/abs/2004.01581
