The objective of this study is to propose a position-distance-related model based on complex networks for the H1N1 epidemic simulation. Situation updates of the H1N1 prevalenced in 2009 show that spreading of the epidemic virus is highly correlative with its position and distance as well. Then in the proposed simulation model, each node in the network is described with not only its edges but also its position and distance. Accordingly, two mechanisms called “growth with position” and “degree and distance based preferential attachment” are introduced in the proposed model that it establishes one connection with likelihood proportional to node’s degree and inversely proportional to the distance between two nodes. Beside the traditional node-growth mode, one called link-growth mode is also introduced. The main advantage of the proposed method is that it is one concise data-driven modeling based on complex networks. Simulation results utilizing the proposed link-growth mode and the traditional node-growth mode show that the two modes are equivalent to each other but from different perspectives. Moreover, compared to the traditional node-growth mode, the proposed link-growth mode is clear and concise.