Modelling disease outbreaks in realistic urban social networks

Abstract

Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions or ad hoc models for the contact process. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free, which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population.

A mobility model for classical swine fever in feral pig populations

“…This phenomenon highlights the importance which long-range mobility has on the spatial extent and overall scale of an outbreak by connecting together 'stepping-stone islands' [30]. This connective feature is commonly found in social networks and network analysis techniques developed for human diseases [6,8,25] may also have application here. The results of Table II and Table III show that long-range contact does occur, with adult male herds increasing the area and number of herds infected.…”

“…The explicit mobility modelling method may also be applicable for capturing the movement of migratory wildlife and the effect which such seasonal movement has on disease spread to domestic animal populations which share specific diseases and habitat with the migratory species. Related simulation models, also with explicit host mobility, have recently been developed to model the spread of human diseases such as pandemic influenza [9,10,14,15,23] and smallpox [8].…”

An individual-based model of hepatitis A transmission

“…Recently, highly detailed individual-based models have been developed for evaluating the effectiveness of control measures for diseases such as pandemic influenza (Germann et al, 2006;Ferguson et al, 2005Ferguson et al, , 2006Longini et al, 2005Longini et al, , 2004Ciofi degli Atti et al, 2008) or fighting back a bioterroristic attack (e.g., by employing smallpox virus) (Eubank et al, 2004;Longini et al, 2006;Riley and Ferguson, 2006;Halloran et al, 2002). As highlighted by Riley (Riley, 2007), the need arises "to develop a simple model of household demographics, so that these largescale models can be extended to the investigation of long-time scale human pathogens".…”

The Effect of Social Mixing Controls on the Spread of Smallpox—A Two-Level Model

“…The concept of small world networks [16,17] is utilized by several researchers to model nonhomogeneous transmission in a population [18][19][20]. Eubank et al [19] develop a detailed large-scale urban traffic simulation, and find that interactions among people form a strongly connected small-world-like graph.…”

“…Eubank et al [19] develop a detailed large-scale urban traffic simulation, and find that interactions among people form a strongly connected small-world-like graph. They examine several response policies and conclude that outbreaks can be contained by a combination of targeted vaccination and early detection.…”