An individual-based networked model with probabilistic relocation of people and vectors among locations for simulating the spread of infectious diseases

Eubank et al. propose to study the spread of infectious disease in large urban environments using dynamic bipartite graph modeling the contact pattern, and computer simulations to estimate the evolution of epidemics. Eubank’s approach requires a detailed knowledge of individuals, daily routine. In our work we would generalize the model by introducing a stochastic relocation of people and vectors among locations, thanks to distribution functions. Computer simulations are used to produce the infection and death processes. Finally, the paper presents two case studies. The first case study emphasizes the effect of using probabilistic relocation in a particular social network, while the second discusses how vector-borne diseases could be taken into account.