论文标题
使用Web搜索查询的高风险用户的移动性对Covid-19 Hotspot的预警预警
Early Warning of COVID-19 Hotspots using Mobility of High Risk Users from Web Search Queries
论文作者
论文摘要
Covid-19破坏了全球经济和人们的福祉，以空前的规模和规模。要遏制这种疾病，一种预测暴发位置的有效预警系统至关重要。研究表明，使用大规模迁移率数据来监测通过人口密度分析（例如，锁定）的影响（例如锁定）的影响。但是，仅使用移动性数据来预测潜在爆发的位置很难。同时，已证明网络搜索查询是疾病扩散的良好预测指标。在这项研究中，我们利用具有通用用户标识符（> 450k用户）的人类移动轨迹（GPS痕迹）和Web搜索查询的唯一数据集，以预测Covid-19的Hotspot位置。更具体地说，进行Web搜索查询分析是为了识别Covid-19收缩高风险的用户，并进一步对这些用户的移动性模式进行了社交联系分析，以量化爆发的风险。使用从日本东京用户收集的数据对我们的方法进行经验测试。我们表明，与仅使用社交联系索引或Web搜索数据分析相比，通过将COVID-19相关的Web搜索查询分析与社交联系网络集成到社交联系网络1-2周，我们能够预测Covid-19 Hotspot位置。这项研究提出了一种新方法，可用于疾病爆发热点的预警系统中，该方法可以帮助政府机构准备有效的策略，以防止进一步的疾病扩散。
COVID-19 has disrupted the global economy and well-being of people at an unprecedented scale and magnitude. To contain the disease, an effective early warning system that predicts the locations of outbreaks is of crucial importance. Studies have shown the effectiveness of using large-scale mobility data to monitor the impacts of non-pharmaceutical interventions (e.g., lockdowns) through population density analysis. However, predicting the locations of potential outbreak occurrence is difficult using mobility data alone. Meanwhile, web search queries have been shown to be good predictors of the disease spread. In this study, we utilize a unique dataset of human mobility trajectories (GPS traces) and web search queries with common user identifiers (> 450K users), to predict COVID-19 hotspot locations beforehand. More specifically, web search query analysis is conducted to identify users with high risk of COVID-19 contraction, and social contact analysis was further performed on the mobility patterns of these users to quantify the risk of an outbreak. Our approach is empirically tested using data collected from users in Tokyo, Japan. We show that by integrating COVID-19 related web search query analytics with social contact networks, we are able to predict COVID-19 hotspot locations 1-2 weeks beforehand, compared to just using social contact indexes or web search data analysis. This study proposes a novel method that can be used in early warning systems for disease outbreak hotspots, which can assist government agencies to prepare effective strategies to prevent further disease spread.
