| 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)
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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 |
FY2021 saw many advancements toward the objectives of the program. The PI published works about the co-evolution of sentiments, behavior, and disease spreading using social media data and a seminal study of Chinese mobility in the first year of Covid-19. Another work by the PI concerned how to represent contact data more efficiently for network epidemiology. Co-I Masuda contributed to several theoretical studies of disease spreading and how to analyze epidemic data. Co-I Ibuka had several publications about Covid-19 in Japan, and its social implications, including a seminal article about movement patterns during the Olympic games. The latter paper was co-authored by co-I Asai, who also co-authored a great number of reports about Covid-19 in Japan. Co-I Beauchemin published work on in-host viral dynamics. Co-I Takayasu published theoretical works on spreading dynamics and data science papers about opinion dynamics.
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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
Our work is continuing along the lines of the proposal. Since Covid-19 has become a real-life laboratory for many of the research ideas of the proposal, some of the work has been changed to follow these developments. For example, Co-I Asai has been heavily involved in monitoring the impact of Covid-19 on Japanese healthcare. Data-driven studies of the Covid-10 epidemics have replaced some of the original plan's emphasis on theoretical and computational modeling, but on the whole, we are covering the research initially anticipated.
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| 今後の研究の推進方策 |
In the future, we aim to extend the scope of our project and delve deeper into the co-evolution of awareness and epidemics, as informed by data. This year, we plan to continue working with Covid-19 data to improve to match reality better. We will refine our network epidemiological vaccination models based on the new data by incorporating experimental game theory. Specifically, we will continue our work on models of various health decisions using game theory and their impact using network epidemiology. We will also explore vaccination games on networks to develop more realistic models. To achieve this, we will simulate different scenarios and identify optimal vaccination strategies using our previously developed model.
Prof. Holme and his team will continue to lead the core analysis, including calibrating our models and integrating results from the different work packages. In parallel to these efforts, we will focus on unifying the outcomes from the work packages to build a comprehensive network-epidemiological theory of the co-evolution of epidemics and behavior.
Additionally, we will explore the impact of different intervention strategies on the spread of epidemics. We will investigate the efficacy of contact tracing, quarantine, and vaccination in reducing the transmission of infectious diseases.
Finally, we aim to provide policymakers with actionable insights and recommendations for designing effective intervention strategies to curb the spread of infectious diseases.
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