Countrywide Origin-Destination Matrix Prediction and Its Application for COVID-19
Countrywide Origin-Destination Matrix Prediction and Its Application for COVID-19
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DOI：
10.1007/978-3-030-86514-6_20
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发表时间：
2021
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影响因子：
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通讯作者：
Renhe Jiang;Zhaonan Wang;Z. Cai;Chuang Yang;Z. Fan;Tianqi Xia;Go Matsubara;H. Mizuseki;Xuan Song
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文献类型：
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作者：
Renhe Jiang;Zhaonan Wang;Z. Cai;Chuang Yang;Z. Fan;Tianqi Xia;Go Matsubara;H. Mizuseki;Xuan Song
建模和预测人体移动性对于智能交通系统、人群管理、灾害响应等各种应用场景具有重要意义。特别是在COVID-19等严重疫情下，不同地区之间的人员流动被视为了解和预测一个国家疫情蔓延的最重要点。因此，在这项研究中，我们收集了大量的人类GPS轨迹数据，覆盖了日本的47个县和模型之间的每对县的日常人类运动与时间序列的起点-目的地（OD）矩阵。然后，考虑到过去几天的历史观测结果，我们通过提出一种名为Origin-Destination Convolutional Recurrent Network（ODCRN）的新型深度学习模型来预测未来一周或多周的全国OD矩阵。它集成了递归和二维图卷积组件来处理顺序OD矩阵中高度复杂的时空依赖性。整个COVID-19期间的实验结果证明了我们提出的方法优于现有的OD预测模型。最后，我们将预测的全国OD矩阵应用于SEIR模型，这是最经典和最广泛使用的流行病模拟模型之一，以预测整个日本的COVID-19感染人数。模拟结果也证明了我们的全国OD预测模型对于COVID-19等大流行情景的高可靠性和适用性。
Modeling and predicting human mobility are of great significance to various application scenarios such as intelligent transportation system, crowd management, and disaster response. In particular, in a severe pandemic situation like COVID-19, human movements among different regions are taken as the most important point for understanding and forecasting the epidemic spread in a country. Thus, in this study, we collect big human GPS trajectory data covering the total 47 prefectures of Japan and model the daily human movements between each pair of prefectures with time-series Origin-Destination (OD) matrix. Then, given the historical observations from past days, we predict the countrywide OD matrices for the future one or more weeks by proposing a novel deep learning model called Origin-Destination Convolutional Recurrent Network (ODCRN). It integrates the recurrent and 2-dimensional graph convolutional components to deal with the highly complex spatiotemporal dependencies in sequential OD matrices. Experiment results over the entire COVID-19 period demonstrate the superiority of our proposed methodology over existing OD prediction models. Last, we apply the predicted countrywide OD matrices to the SEIR model, one of the most classic and widely used epidemic simulation model, to forecast the COVID-19 infection numbers for the entire Japan. The simulation results also demonstrate the high reliability and applicability of our countrywide OD prediction model for a pandemic scenario like COVID-19.