JpGU-AGU Joint Meeting 2020

Presentation information

[J] Poster

U (Union ) » Union

[U-24] COVID-19, the Earth's Environment and Disaster

convener:Jun Matsumoto(Deaprtment of Geography, Tokyo Metropolitan University), Yukihiro Takahashi(Department of Cosmosciences, Graduate School of Science, Hokkaido University), Akira Wada(Tokyo Institute of Technology), Manabu D. Yamanaka(Research Institute for Humanity and Nature / Professor Emeritus of Kobe University)

[U24-P02] Ensemble Data Assimilation of COVID-19 Epidemic Model: Relationships between Infectivity and Earth Environments

*Shunji Kotsuki1, Atsushi Okazaki2 (1.Center for Environmental Remote Sensing, Chiba University, 2.Department of Meteorology & Atmospheric Science, Penssylvania State University)

Keywords:COVID-19, Epidemiological Model, Data Assimilation, Infectivity, Satellite Observations, Atmospheric Reanalysis Data

The worldwide epidemic of COVID-19 has required more understandings of its infectivity and impacts on Earth environments. This study proposes a method enabling such assessments by integrating mathematical approaches and Earth environments. We first developed a modified epidemiological model based on a commonly used compartment model. The model assigns population into five compartments, Susceptible, Exposed, Infectious, Recovered, and Death; hereafter SEIRD model). In this outbreak, there are daily reports of COVID-19-induced deaths, as opposed to influenza epidemics. Hence we updated the commonly used SEIR model to additionally consider deaths. We conducted ensemble data assimilation of the SERID model for individual countries using daily reports of new cases and deaths as observation data. The data assimilation revealed that time series of infectivity of COVID-19 clearly corresponded with political decisions such as the rock-downs and economic activity resume in the U.S., and economic restraint in Japan. Additionally, satellite observations of NO2 also supported the economic restraints. Based on worldwide data assimilation experiments and atmospheric data, we are now investigating the relationships between COVID-19 infectivity and environments, which is one of COVID-19's uncertainty. This presentation will include the most recent progress up to the time of the conference.