A simulation study of H1N1 space-time epidemic based on agent-based modeling

BACKGROUD: Since Mexico reported the first case of Influenza A H1N1 influenza patients in March 2009, Influenza A H1N1 flu spreads rapidly around the world and threats seriously to human health. OBJECTVIES: (1) Establishing an Agent-based Model (ABM) of H1N1 transmission, simulating and predicting the distribution of location, extent and development of the law of H1N1 to explore the space-time propagation of H1N1. (2) Simulating how many people will be infected under different disease control strategies. (3) Helping decision-makers decide on the best strategy to mitigate the spread of infection. METHODS, Simulation core is built H1N1 propagation model base on ABM. This model consists of Agent, the environment and rules of three parts. H1N1 influenza has contagious, the short incubation period and the spread of strong characteristics. The paper is divided into five types of Agent according to these characteristics. The first is the health of Agent; The second is high-risk Agent; The third Agent is that H1N1 influenza virus has been transmitted but not yet diagnosed; The fourth Agent is that influenza A H1N1 influenza have been confirmed infected; The fifth is death Agent. Environment is the space in which Agent. It can be a two-dimensional grid, can be a network, can also be expressed by the vector or raster spatial data. In this paper we use the vector data. Rules are a source of Agent intelligence, Agent for all acts must follow the rules. H1N1 model includes acting rules, the state transformation rules and interact rules between Agents an environment. The acting rule is random movement rules in this article. Assuming a distance as the critical distance transmission of H1N1, more than this distance will not be infected with H1N1, but the closer the distance the higher rate of infection. The state transformation rule is SEIDR model. The interact rules between Agents an environment is the Agent and GIS integration. The paper makes Agent Analyst as the integration pla- - tform. The three rules in the whole simulation process is a whole and synchronous parallel occurrence. We can evaluate the results of different control measures by adjusting the rules´ parameters during the simulation. Finally, we conducted an empirical study of Kunming as an example. RESULTS Different intensity of preventive measures to control the epidemic H1N1 plays a decisive role.