Modelling the effect of lockdown

Kamei, H.; Sato, A.

This note models the effect of the lockdown during the first wave of COVID-19. We use SEIR type of model with a certain time lag between infection and becoming infectious. Firstly we compare the timing of the change of the coefficient of infection, growth rate of confirmed cases corresponds to the change of mobility index, and secondly we assume the change of the coefficient of infection, activity index $beta$ (analogous to $R_0$) and fit the parameter to reproduce the actual number of confirmed cases. Finally, we assume that the activity index $beta$ is proportional to the square of the mobility and fit the parameters. The curves in various cuontries fits reasonably well in any cases, but estimating $beta$ from various parameters (including temperature) remains as an important task.