Prediction of Infuenza Epidemics and Assessment of Treatment using Mathematics Models

2022 Fiscal Year Final Research Report

• Project/Area Number: 19K16428
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 47060:Clinical pharmacy-related
• Research Institution: Kyoto Pharmaceutical University
• Principal Investigator: Chisaki Yugo 京都薬科大学, 薬学部, 助教 (30781356)
• Project Period (FY): 2019-04-01 – 2023-03-31
• Keywords: インフルエンザ / 流行予測 / 数理モデル / SIRモデル / NONMEM

Outline of Final Research Achievements

Influenza is a type of disease that causes periodic epidemics, and SIR models based on epidemic processes have been proposed.The objectives of this study were to evaluate factors related to weather that affect influenza epidemics and to develop a model for predicting epidemics using the SIR model. It was shown that there is a negative correlation between the number of reports per fixed point and the average temperature. Population analysis was conducted and model building was examined, but convergence was not sufficient. By examining various models, we were able to construct a model with predictability under some conditions, however the model construction with validity was not sufficient, partly because the amount of data was smaller than initially expected. We will accumulate more data in the future and strive to disseminate information that can be returned to clinical practice.

Free Research Field

医療薬学

Academic Significance and Societal Importance of the Research Achievements

本研究成果として、定点当たり報告数と平均気温度には負の相関関係があることが示された。平均気温と平均蒸気圧に強い相関がみられることからも、Finalモデルとして平均気温のみのモデルとなったことは妥当であると考えられる。母集団解析によるSIRモデルを検討することで一部の条件下では予測性の高いモデル構築ができたが、当初の想定よりもデータ量が少ないこともあり、妥当性の高いモデル構築は十分ではなかった。り詳細なインフルエンザ件数の報告を収集することでより良いモデル構築ができる可能性が示唆された。本研究結果は今後のSIRモデルによる流行予測の一助となると考えられる。