Infectious Disease Data Analysis
Currently, a new coronavirus is raging and is having a strong impact that forces us to change our life style. Also fresh in our minds are the H1N1 novel influenza in 2009 and Ebola in 2014. Because we have no immunity to these emerging viruses, we could not defend ourselves against them. So, we have a very high probability of becoming infected when we are exposed to these viruses. Mathematical models have been studied for a long time to predict the future spread of infectious diseases based on information such as the infectivity of the virus, but it is difficult to translate these predictions into concrete countermeasures due to Japan's complex geography and transportation system. We have built a virtual city on a supercomputer, in which more than one million agents with personal profiles (gender, age, occupation, family information, etc.) are placed, where trains run, companies, schools, supermarkets, parks, restaurants, etc. are built, and where the year's traffic can be monitored every minute. We are conducting research on agent-based simulations to evaluate the spread of infection and the effectiveness of countermeasures through simulation.
Risk assessment through exposure analysis:
In With-Corona era, risk assessment at crowded events (so-called “mass gathering events”) is an important issue. When an infected person enters a stadium, whether the spread of infection occurs depends on the behavior of people in the stadium. We have modeled the human behavior patterns of people in different locations, assessed the risk of infection for each behavior. We can assess the effectiveness of each of concrete countermeasures such as the use of thermography to catch infected people before entering the stadium (symptomless patients will be allowed in), wearing masks, etc. A solution-oriented risk assessment study is being conducted as a collaborative research.
COVID-19 risk assessment at the opening ceremony of the Tokyo 2020 Olympic Games：
The 2020 Olympic/Paralympic Games have been postponed to 2021, due to the COVID-19 pandemic. We developed a model that integrated source–environment–receptor pathways to evaluate how preventive efforts can reduce the infection risk among spectators at the opening ceremony of Tokyo Olympic Games. We simulated viral loads of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emitted from infectors through talking/coughing/sneezing and modeled temporal environmental behaviors, including virus inactivation and transfer. Monte Carlo simulations were used to predict the number of new infections with and without preventive measures, and to evaluate the risk of infection at the opening ceremony and the risk reduction effect of the measures.