THE USE OF GIS and AGENT BASED MODELS IN ANIMAL EPIDEMIOLOGY

Aug 19, 2015



Person, place, time: these are the basic elements of outbreak investigations and epidemiology. Historically, however, the focus in epidemiologic research has been on person and time, with little regard for the implications of place or space even though disease mapping has been done for over a hundred years. The development of geographic information systems (GISs) over the last 20 years has provided a more powerful and rapid ability to examine spatial patterns and processes.This, in turn, has fostered the discussion of such policy-relevant issues as health services and planning, as well as the use of GISs for epidemiologic investigations and disease surveillance.Spatial epidemiology issues are outstandingly important, particularly the viral spread through populated areas is believed to be one of the major concerns. The incidence and prevalence of infectious diseases in a given population, with varied geographic and demographic settings, need to be analyzed over the spatial and temporal domain in order to build dynamic[caption id="attachment_158" align="alignnone" width="300"]Netlogo Java ABM Netlogo Java ABM[/caption] models that provide a global insight of outbreaks' behavior.Transmission of an infectious disease may occur through several pathways: by means of contact with infected individuals, by water, airborne inhalation, or through vector-borne spread. However, for the purpose of this study, the direct contact of susceptible individuals with an infected one will be considered as the main transmission medium of contagious diseases. Therefore, it is assumed that infectious diseases are diffused from individual to individual following a network of contact between them. Since this contact usually takes place in a geographical space, it is fairly natural to expect that the space plays an important role in the dynamics of infectious diseases (3). Clear evidences that some infectious diseases in animal populations spread geographically are the two well-known recent examples of communicable disease spatial advance in the world, these are Highly Pathogenic Avian Influenza (H5N1) and foot and Mouth Disease (FMD). For this reason, it is required to understand the complex dynamics of contagious illnesses given certain spatial environments.One of the challenges that face geographers, epidemiologists and computer scientists working in the field of spatio- temporal modeling, is trying to understand the complexity of the spread of diseases. The search for an understanding of the non-linear behavior of epidemics' spread and their causes in order to control them, has resulted in several attempts to model and predict the pattern of many different communicable diseases through a population. Models can be defined as an abstraction of the real world, regardless of type or complexity, they are basically simplifications of a real-life system, which can contain only some of the essential elements of it – as determined by the researcher -, models are not exact reproductions of reality and can be interpreted by different people in different ways.In spatial epidemiology, models have been primarily used to facilitate an understanding of the complexity of the interaction between the spread of a disease among different individuals and its impact on ecosystems and biodiversity.It is for these reasons that the objective of this study is to develop and implement an agent-based modeling approach for the spread of a communicable disease. The theoretical framework will be implemented in a case study of Foot and Mouth Disease in Lebanon to allow the creation, representation and execution of a communicable disease propagation simulation over space and time and in an environment.One of the most important factors that this study considered is the complexity of mobile individuals in an undefined setting with no social identifications to differ between agents, their exchanges during the commuting time and some of the possible interactions among them in specific locations where there interactions are dynamic.Hany Imam Hany Imam, GIS Information Management Officer at United Nations Resident Coordinators Office in Lebanon. Connect with Hany