Multiagent Simulation of Seasonal Influenza from Preinfectious People in Closed Spaces

This study proposes a discrete mathematical Susceptible–Exposed–Preinfectious–Infectious–Recovered (SEPIR) states model for seasonal influenza. In a previous study, focusing on infections by preinfectious people using preexisting data, the author showed that the super-spreading of seasonal influenza occurred before the day that the first patients were discovered (D-day). In addition, when people do not take precautionary measures, the infectivity rate (from preinfected people) was determined as 0.041. After D-day in the community, the implementation of countermeasures was observed to reduce the infectivity rate to 0.002 and 0.013 in working and living spaces, respectively. The number of infectious people can be estimated by summing up each group in the community. This study performed a multiagent simulation (MAS) of seasonal influenza from preinfectious people in closed spaces based on decomposability. Then, the basic simulation is validated and the appropriateness of infective rates, changed infectivity rates, and near decomposability is confirmed.