Computational modeling and statistical analyses on individual contact rate and exposure to disease in complex and confined transportation hubs

Crowded transportation hubs such as metro stations are thought as ideal places for the development and spread of epidemics. However, for the special features of complex spatial layout, confined environment with a large number of highly mobile individuals, it is difficult to quantify human contacts in such environments, wherein disease spreading dynamics were less explored in the previous studies. Due to the heterogeneity and dynamic nature of human interactions, increasing studies proved the importance of contact distance and length of contact in transmission probabilities. In this study, we show how detailed information on contact and exposure patterns can be obtained by statistical analyses on microscopic crowd simulation data. To be specific, a pedestrian simulation model-CityFlow was employed to reproduce individuals' movements in a metro station based on site survey data, values and distributions of individual contact rate and exposure in different simulation cases were obtained and analyzed. It is interesting that Weibull distribution fitted the histogram values of individual-based exposure in each case very well. Moreover, we found both individual contact rate and exposure had linear relationship with the average crowd densities of the environments. The results obtained in this paper can provide reference to epidemic study in complex and confined transportation hubs and refine the existing disease spreading models.