Infectious disease and climate change: a fuzzy database management system approach

Infectious diseases are reemerging globally, many of them being climate-related. The integration of remote sensing and disease outbreak data along with GIS and artificial intelligence approaches provides the tools for predicting future disease outbreaks. A fuzzy database management system (FDBMS) has been constructed for this purpose, storing disease outbreaks and a variety of parameters such as precipitation, temperature, population density, elevation and other variables. The FDBMS is able to search the database and provide disease risk assessments based upon crisp and fuzzy conditions stated about spatial, temporal, climatic and other parameters. The fuzzy search is generated either by using a graphical user interface (GUI) or a fuzzy query language (FQL). FQL is an extension to the well-known relational structural query language (SQL), and it allows the user to make complex queries. The FDBMS is able to display the locations of previous disease outbreaks on a world map in the system GUI. Currently, nine years of U.S. disease data from the Center for Disease Control (CDC) and from the state of Texas are stored in the database. A major expansion to global datasets is in progress, and international health agencies are asked to contribute to this effort.