title: Understanding spatial connectivity of individuals with non-uniform population density.
abstract: We construct a two-dimensional geometric graph connecting individuals placed in space within a given contact distance. The individuals are distributed using a measured country's density of population. We observe that while large clusters (group of individuals connected) emerge within some regions, they are trapped in detached urban areas owing to the low population density of the regions bordering them. To understand the emergence of a giant cluster that connects the entire population, we compare the empirical geometric graph with the one generated by placing the same number of individuals randomly in space. We find that, for small contact distances, the empirical distribution of population dominates the growth of connected components, but no critical percolation transition is observed in contrast to the graph generated by a random distribution of population. Our results show that contact distances from real-world situations as for WIFI and Bluetooth connections drop in a zone where a fully connected cluster is not observed, hinting that human mobility must play a crucial role in contact-based diseases and wireless viruses' large-scale spreading.
authors.affiliation: Center for Complex Network Research, Department of Physics, Biology and Computer Science, Northeastern University, Boston, MA 02115, USA.
authors.forename: Pu
authors.initials: P
authors.lastname: Wang
authors.forename: Marta C
authors.initials: MC
authors.lastname: González
mesh_terms: D000465:Algorithms; D040421:Cell Phone; D016000:Cluster Analysis; D006801:Humans; D011156:Population Density; D013269:Stochastic Processes