Vigfusson Ymir, Karlsson Thorgeir A, Onken Derek, Song Congzheng, Einarsson Atli F, Kishore Nishant, Mitchell Rebecca M, Brooks-Pollock Ellen, Sigmundsdottir Gudrun
Simbiosys Lab, Department of Computer Science, Emory University, Atlanta, GA 30322;
School of Computer Science, Reykjavik University, 101 Reykjavik, Iceland.
Proc Natl Acad Sci U S A. 2021 Feb 9;118(6). doi: 10.1073/pnas.2005241118.
Epidemic preparedness depends on our ability to predict the trajectory of an epidemic and the human behavior that drives spread in the event of an outbreak. Changes to behavior during an outbreak limit the reliability of syndromic surveillance using large-scale data sources, such as online social media or search behavior, which could otherwise supplement healthcare-based outbreak-prediction methods. Here, we measure behavior change reflected in mobile-phone call-detail records (CDRs), a source of passively collected real-time behavioral information, using an anonymously linked dataset of cell-phone users and their date of influenza-like illness diagnosis during the 2009 H1N1v pandemic. We demonstrate that mobile-phone use during illness differs measurably from routine behavior: Diagnosed individuals exhibit less movement than normal (1.1 to 1.4 fewer unique tower locations; [Formula: see text]), on average, in the 2 to 4 d around diagnosis and place fewer calls (2.3 to 3.3 fewer calls; [Formula: see text]) while spending longer on the phone (41- to 66-s average increase; [Formula: see text]) than usual on the day following diagnosis. The results suggest that anonymously linked CDRs and health data may be sufficiently granular to augment epidemic surveillance efforts and that infectious disease-modeling efforts lacking explicit behavior-change mechanisms need to be revisited.
疫情防范取决于我们预测疫情发展轨迹以及在疫情爆发时推动传播的人类行为的能力。疫情期间行为的变化限制了使用大规模数据源（如在线社交媒体或搜索行为）进行症状监测的可靠性，否则这些数据源可以补充基于医疗保健的疫情预测方法。在此，我们使用2009年甲型H1N1流感大流行期间手机用户及其流感样疾病诊断日期的匿名关联数据集，测量了反映在手机通话记录（CDR）中的行为变化，CDR是一种被动收集的实时行为信息来源。我们证明，患病期间的手机使用情况与日常行为有显著差异：被诊断出患病的个体在诊断前后2至4天内的移动量比正常情况少（独特基站位置平均少1.1至1.4个；[公式：见原文]），拨打电话次数也更少（少2.3至3.3次；[公式：见原文]），而在诊断后的第二天，他们打电话的时长比平时更长（平均增加41至66秒；[公式：见原文]）。结果表明，匿名关联的CDR和健康数据可能具有足够的粒度来加强疫情监测工作，并且需要重新审视缺乏明确行为变化机制的传染病建模工作。
