日時：　2021年 11月 12 日 (金曜日)  16:45 -- 18:15
Date:      November 12, 2021 (Fri.) 16:45 -- 18:15

講演者： 山本 奈央 氏（アリゾナ州立大学）

題目　： The differential equation models of COVID-19 epidemic

概要：
Infectious disease modeling is attracting widespread interest due to the coronavirus disease (COVID-19) global pandemic. While ordinary differential equations such as the SIR (Susceptible-Infectious-Recovered) model and its advanced version, the SEIR (Susceptible-Exposed-Infectious-Recovered) model, are frequently used, there are not many models that use partial differential equations. We modeled the meta-population dynamics of COVID-19 in Arizona using ODE and the spatio-temporal dynamics using PDE with empirical data on human mobility retrieved from Google Community Mobility Reports. Both our ODE and PDE models showed that mobility restrictions help to reduce the size of an epidemic. Quantifying the impact of mobility restrictions together with the vaccination rate on minimizing the epidemic impact can provide useful insights for policy makers.

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