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In the COVID-19 pandemic, keeping a two-metre physical distance (called  social distancing ) from others is a critical action to limit the amount of social contact among individuals. Thus, regulating the number of persons in a space is one means to limit social contact and ensure physical distancing among people. In addition to the privacy concerns of individuals’ locations, the lack of elevation information can result in false positive cases for people who are horizontally close but vertically apart beyond the social distance. Therefore, we develop a normative model of the statistical distribution of physical distances to estimate the number of persons not social distancing in a three-dimensional complex built space from the current number of persons in the space (i.e. population density) present on an hourly basis. We conduct an empirical case study in the districts around the central stations of 13 of Japan’s prefectures. To determine the number of people not social distancing in these districts, the proposed model uses open data such as the number of persons before the national emergency declaration, the ratio of the number of persons after the declaration to that before, and the floor area ratio specified by land use regulations in these districts.

A normative model to estimate the number of persons not social distancing in a 3D complex built space