Development of the analytical framework of spatio-temporal networks using large-scale human mobility data

2021 Fiscal Year Final Research Report

• Project/Area Number: 18K11462
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 61040:Soft computing-related
• Research Institution: Tohoku University
• Principal Investigator: Fujiwara Naoya 東北大学, 情報科学研究科, 准教授 (00637449)
• Project Period (FY): 2018-04-01 – 2022-03-31
• Keywords: 人流 / 地理情報科学 / 数理モデル / 感染症

Outline of Final Research Achievements

In this project, the research regarding human mobility and interregional interactions through human mobility has been conducted. Considering features of GPS data, cell-tower-based data, and questionnaire-based human mobility data, studies on such as delineation based on the human mobility network analysis have been conducted. This framework has been applied to e.g. analyses of change of mobility after the COVID-19 pandemic, and the correlation between human mobility and spread of COVID-19 has been investigated. Mathematical models on spatial spread of infectious diseases and formation of cities have been introduced and studied, which fascilitates the understanding of the human mobility.

Free Research Field

複雑ネットワーク科学

Academic Significance and Societal Importance of the Research Achievements

人流は都市における人間活動を理解する上で重要な役割を果たす。例えば都市における経済活動はその都市内外の人流と強い関係がある。また、感染症は人の接触により伝播するので、人流データから感染伝播の地理的特徴を明らかにできると期待される。本課題は、さまざまな人流データの解析の基盤を提供するとともに、人流と感染拡大の関係や都市形成と人流の関係などを理論的にも理解することを目指すものであり、人流に関連する社会における様々な現象の理解に貢献する。