Modeling the Effects of Transient Populations on Epidemics

A large number of transients visit big cities on any given day and they visit crowded areas and come in contact with many people. However, epidemiological studies have not paid much attention to the role of this subpopulation in disease spread. In the present work, we extend a synthetic population model of Washington DC metro area to include leisure and business travelers. This approach involves combining Census data, activity surveys, and geospatial data to build a detailed minute-by-minute simulation of population interaction. We simulate a flu-like disease outbreak both with and without the transient population to evaluate the effect of the transients on outbreak size and peak day in terms of number of residents infected. Results show that there are significantly more infections when transients are considered. We also evaluate interventions like closing big museums and encouraging use of hand sanitizers at those musuems. Surprisingly closing musuems does not result in a significant difference in the epidemic. However, we find that if the use of hand sanitizer reduces the infectivity and suceptibility to 80% or 60% of the original values, it is as effective as closing museums for a few days or entirely eliminating the effect of transients. If infectivity and susceptibility are reduced to 40% or 20%, it reduces the number of resident infections over the period of 120 days by 10% and 13%.