Infectious diseases are reemerging globally, many of them beingclimate-related. The integration of remote sensing and disease outbreakdata along with GIS and artificial intelligence approaches provides thetools for predicting future disease outbreaks. A fuzzy databasemanagement system (FDBMS) has been constructed for this purpose, storingdisease outbreaks and a variety of parameters such as precipitation,temperature, population density, elevation and other variables. TheFDBMS is able to search the database and provide disease riskassessments based upon crisp and fuzzy conditions stated about spatial,temporal, climatic and other parameters. The fuzzy search is generatedeither by using a graphical user interface (GUI) or a fuzzy querylanguage (FQL). FQL is an extension to the well-known relationalstructural query language (SQL), and it allows the user to make complexqueries. The FDBMS is able to display the locations of previous diseaseoutbreaks on a world map in the system GUI. Currently, nine years ofU.S. disease data from the Center for Disease Control (CDC) and from thestate of Texas are stored in the database. A major expansion to globaldatasets is in progress, and international health agencies are asked tocontribute to this effort
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