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Insects are strongly influenced by meteorological variables in their natural environment. In agriculture, mathematical models have been developed to understand and forecast the cycle of pests based on climate data. By this manner, with the goal of reduce and rationalize plant chemical treatments, agrometeorological models have been realized to estimate the length and starting times of parasites phenological phases. In Sicily a new network of 95 GSM meteorological stations and a specific mathematical model for Aonidiella aurantii are used by Sicilian Agrometeorological Information System (SIAS) for the integrated pest management program of citrus orchards in the Island. As the plants parasites, vector borne diseases are influenced by climate in their appearance and abundance. In lights of the benefits that could derive from a model for the control of Leishmania vectors, SIAS experiences in modelling were used to develop a deductive model for Phlebotomus perniciosus which represents the major vector of human and canine leishmaniasis in Sicily.

In recent years leishmaniasis has become a serious Public Health problem in Italy. The coexistence of infected dogs, vectors and humans, makes urban areas suitable environment for the spread of this zoonotic disease. With the purpose to improve the current system for the control of leishmaniasis in urban areas, the authors report their experiences carrying out a Health Information System (HIS) for the surveillance of the disease in the city of Messina. The HIS project is built on a dataset containing geographical data on urban environment, census tracts at parish level and data of human and canine leishmaniasis cases reported in the last years. The HIS allows the spatial representation of the disease occurrence and can be used as a novel epidemiological tool to perform area-based surveillance.

Geographic information systems (GIS) and remote sensing (RS) technologies are being used increasingly to study the spatial and temporal patterns of some parasitic diseases of medical and veterinary importance. At the same time, the incorporation of GIS in this field shows the scarcity of the data and images available, which sometime discourage researchers that still look at GIS as a system too difficult and unusable for medical study. Aware of this problem and supported by success of earlier MMDb's for Africa, Asia and South America, the authors' aim is to construct and offer an MMDb for Europe. The initial MMDb is composed with vector images covering an area situated from -11 degrees-70 degrees N to 58 degrees-30 degrees E. Specifically, data layers include: a) Global Moderate-Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16 days at 250 m spatial resolution designed to provide consistent spatial and temporal comparisons of vegetation conditions, supplied in the MMDb as seasonal and annual composite images from 2000 to 2003, b) MODIS Land Surface Temperature (LST) calculated from daytime and nighttime observations at 8 day intervals at 1 km spatial resolution, supplied in the MMDb as seasonal and annual composites images for day (maximum) temperatures, night (minimum) temperatures from 2000 to 2003, c) GTOPO30 Digital Elevation Model (DEM) at 1 km spatial resolution, d) United States Geological Survey (USGS) Land use/land cover scheme, e) USGS actual and potential evapotranspiration supplied for all 12 months as a grid at 50 km spatial resolution, f) USGS precipitation showing the amount of rainfall for all 12 months supplied as a grid at 50 km spatial resolution, g) USGS shapefiles of administrative and political boundaries, cities, towns, villages, lakes, rivers, streams, road, railroads and more. The MMDb projection will be in geographic latitude-longitude, decimal degree format. This global format is most commonly used for public access map database resources and can be readily re-projected as needed for compatibility with various national mapping systems. There is no "required" software, and end users need only common commercial GIS software packages that have mutual import-export functions. Additionally, the MMDb is meant to be a dynamic resource that end users may improve and modify with other regional data.