Influenza epidemic prediction using a dynamical model

2015 Fiscal Year Final Research Report

• Project/Area Number: 25730181
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Life / Health / Medical informatics
• Research Institution: The Institute of Statistical Mathematics
• Principal Investigator: SAITO Masaya 統計数理研究所, 大学共同利用機関等の部局等, 特任准教授 (00470047)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: 感染症数理モデル / データ同化 / インフルエンザ流行予測

Outline of Final Research Achievements

This research attempted to develop an influenza epidemic prediction model in which transmission dynamics is incorporated aiming at improving the operated alert system based on statistical model. Our system is based on coupled SIR model where each component corresponds to each prefecture of Japan. Although the coupled model outperforms a set of independent SIR models in the sense that the confidence interval is narrowed, there is no significant difference in the mean. Therefore I have concluded that the planned approach may not contribute to the improvement of prediction. We also have tried to apply our approach to another disease, rubella, and showed that 2012/13 minor epidemic is reproduced.

Free Research Field

データ同化，天体力学