Epidemic risk assessment from geographic population density

Abstract

The geographic distribution of the population on a region is a significant ingredient in shaping the spatial and temporal evolution of an epidemic outbreak. Heterogeneity in the population density directly impacts the local relative risk: the chances that a specific area is reached by the contagion depend on its local density and connectedness to the rest of the region. We consider an epidemic spreading in an urban territory subdivided into tiles (i.e., census blocks) of given population and demographic profile. We use the relative attack rate and the first infection time of a tile to quantify local severity and timing: how much and how fast the outbreak will impact any given area. Assuming that the contact rate of any two individuals depends on their household distance, we identify a suitably defined geographical centrality that measures the average connectedness of an area as an efficient indicator for local riskiness.

The Fitness-Corrected Block Model, or how to create maximum-entropy data-driven spatial social networks

“…In particular, we envision its application to generate geographic networks informed by census data, contact surveys, and geospatial data. Indeed, the phenomenological model described at the end of this section has already been employed to develop a realistic social network at the urban scale 9 and to study the spread of an epidemic process 15 – 17 , on it.…”