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Evacuation simulation can greatly ease the cost of money and material in fire case by using computer. Integrating ABM and GIS technology can not only recurrent the evacuation process, but also analyse optimal evacuation route, optimize the supermarket layout by GIS spatial analysis functions. A model is used to determine the action rules of evacuation staff, simulate the evacuation process on Agent Analysis platform and get the change trend of people quantity over time.

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 platform. 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.

In 1989, HIV was detected amongst injecting drug users (IDUs) in Yunnan province. Needle sharing drove the epidemic and HIV spread rapidly to IDUs in neighboring cities and along drug trafficking routes. By 2002, HIV was present amongst IDUs in all mainland Chinese provinces. It is believed that IDUs may have been the core source for all later sub-epidemics in China. Agent-based modeling (ABM) is the dominant paradigm in social complex network simulation which allows one to simulate the complex systems emerge from the bottom-up are composed of a multitude of heterogeneous objects called agents. This article puts forward an HIV/AIDS spatial and temporal transmission model of IDUs based on the multivalent system and geographic information systems (GIS) in an urban environment, and simulates the HIV/AIDS spatial and temporal transmission process among injection drug users during 10 years on the Repast Simphony1.2 platform. In the model, the crowd is classified into 5 types: healthy person, HIV person, AIDS person, IDU person and HIV-IDU person. Individuals represented by agents are associated to places where they interact with each other. The relationship among different agents is described with random social network. To better represent individuals in reality, each agent has its only sex, age, career, education, geographic location and other attributes. In each time step, the model defines these agents' specific behavioral rules. The model is implemented using the propagation of HIV/AIDS among injection drug users in Yunnan province southwest of China as a case study. The simulation results show that the number of initial HIV in injection drug users, the proportion of needle sharing and individual social impact have influence on the spread of HIV/AIDS in Kunming. The results also reveal the increasing HIV/AIDS transmission among injection drug users and interpret the necessity of carrying out solutions to contain the transmission of HIV/AIDS.

Having analyzed the current status and existing problems of Geographic Information Systems (GIS) applications in epidemiology, this chapter proposes a method to establish a spatial decision support system (SDSS) for the prevention of epidemic diseases by integrating the COM GIS, spatial database, gps, remote sensing, and communication technologies, as well as ASP and ActiveX software development technologies. One important issue in constructing the SDSS for epidemic disease prevention concerns the incorporation of epidemic spread models in a GIS. The chapter begins with a description of the capabilities of GIS in epidemic prevention. Some established models of an epidemic spread are studied to extract essential computational parameters. A technical schema is then proposed to integrate epidemic models using a GIS and relevant geospatial technologies. The GIS and modeling platforms share a common spatial database and the modeled results can be visualized spatially by desktop and Web clients. A complete solution for establishing the SDSS for epidemic disease prevention based on the model integrating methods and the ArcGIS software is suggested in this chapter. The proposed SDSS comprises several sub-systems: data acquisition, network communication, model integration, epidemic disease information spatial database, epidemic disease information query and statistical analysis, epidemic disease dynamic surveillance, epidemic disease information spatial analysis and decision support, as well as epidemic disease information publishing based on the Web GIS technology. The design process and sample VC and VB programming codes of the epidemic case precaution are used as an example to illustrate the basic principles and methods of the system development that integrates GIS functions with models of epidemic spread. A case study of AIDS in the Yunnan Province of China exemplifies the systems spatial analytical functions through its spatial database access and statistical analysis tools.

Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.