| 研究課題/領域番号 |
21H04595
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| 研究機関 | 神戸大学 |
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研究代表者 |
Holme Petter 神戸大学, 計算社会科学研究センター, リサーチフェロー (50802352)
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| 研究分担者 |
高安 美佐子 東京工業大学, 科学技術創成研究院, 教授 (20296776)
井深 陽子 慶應義塾大学, 経済学部(三田), 教授 (20612279)
増田 直紀 早稲田大学, 理工学術院, 教授(任期付) (40415295)
浅井 雄介 国立研究開発法人国立国際医療研究センター, 国際感染症センター, 研究員 (70779991)
Beauchemin Catherine 国立研究開発法人理化学研究所, 数理創造プログラム, 副プログラムディレクター (70898931)
村田 剛志 東京工業大学, 情報理工学院, 教授 (90242289)
上東 貴志 神戸大学, 計算社会科学研究センター, 教授 (30324908)
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| 研究期間 (年度) |
2021-04-05 – 2025-03-31
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| キーワード | Network epidemiology / Network science / Theoretical epidemiology / Game theory / Behavioral modeling |
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| 研究実績の概要 |
During FY 2022, we published several papers on the core topics of this research program. For example, we published a paper about how to use previous observations of influenza for forecasting COVID-19 outbreaks and how to automate the extraction of epidemic-relevant information from doctors' reports by AI. Other works covered general models of spreading processes and how to balance breadth and depth in contact tracing if the goal is to find the source of an infection.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
This project follows the outline of the original research program relatively closely. Some advances we made were beyond the scope we could originally predict, such as the use of language models for data extraction. Others are maybe slightly altered. We do, for example, not now intend to build models of behavioral feedback on temporal network models (since these assume data of human mobility that has a much higher resolution than available. Rather, we use somewhat more mainstream, aggregated models.
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| 今後の研究の推進方策 |
Our research follow the general research trends. The results from the present project is pointing towards integration with models from artificial intelligence and more information-rich representations.
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