Per capita seafood consumption is increasing, not only in the U.5., but also worldwide. This includes the consumption of local and, more recently, imported species of fish and shellfish. Concomitantly, the prevalence and incidence of diseases associated with seafood ingestion (infectious and Marine Seafood Toxin (MST)-associated) appear to be expanding beyond their traditional boundaries of island and coastal communities. Recent evidence links global climate changes with the geographic extent of the algal blooms associated with MST production. All these factors increase the potential risk through seafood consumption for the MST-associated diseases in human communities. Infectious disease surveillance systems utilize diagnostic methodologies and resources to identify infectious disease outbreaks associated with seafood consumption and to implement prevention activities. Such a model does not exist for the MST Diseases, including the most commonly reported disease, Ciguatera. The lack of epidemiological data for these disease has severely hampered investigation and assessment of the extend of the problem. At present, surveillance of these diseases is local and anecdotal, at best. There is a tremendous need for accurate surveillance data, localized not only in time, but in space, to understand and prevent the impact of these diseases on human populations. The multi-dimensional, multi-scaled and multi-variate characteristics of these diseases are not suited to conventional methods of epidemiology. GIS is designed to handle and model complex phenomena, such as the epidemiology of the MST Diseases. This three-year application seeks to establish a model MST Surveillance Network, which focuses on the MST disease Ciguatera in Dade County (Florida) to evaluate its disease burden in a endemic education, outreach and the groundwork for primary prevention. GIS will be used as the main tool for managing, analyzing and presenting the data collected from the Surveillance Network and other sources. GIS will allow the identification of potential spatial and temporal patterns of Ciguatera in human populations, which will promote a more accurate understanding of their impact. Incorporation of additional environmental data such as the geographic local of toxic reefs, as well as the oceanographic and atmospheric data, into GIS will permit predictive capabilities for the future prevention of Ciguatera and the other MST diseases in human populations.
