Forecast of the COVID-19 outbreak, collapse of medical facilities, and lockdown effects in Tokyo, Japan

Yoshiyuki Sugishita; Junko Kurita; Tamie Sugawara; Yasushi Ohkusa

The SIR model is too simple to incorporate households, firms or schools. It is a completely mixed model. It therefore ignores some difference inside and outside of those groups. It can adjust contact patterns to mimic some policies including lockdowns or school closures as in the present study. A model highlighting differences inside and outside of those groups is an individual-based model (IBM), which mimics movements and contacts of individuals. It can therefore evaluate behavioral changes of individuals directly [7] [8] [9] [10] 18] . Therefore, we must use IBM for evaluation of a lockdown instead of a SIR model. No IBM exists for COVID-19 but an IBM exists for pandemic influenza. Especially, the most precise IBM, RIBM, has been developed in Japan using actual data of transportation [18, 19] . It indicated that lockdown with 60% voluntary restriction to going out can reduce prevalence by 40 percentage points for pandemic flu [19] . Therefore, it shared the same result that 60% voluntary restriction out of trips outside the home can avoid collapse of medical facilities with the present study for COVID-19.