Health risk assessment of zoonotic infections agents through plant products in areas with high livestock pressure

In areas where there is a high livestock pressure, small variabilities in the infection agents distributions can lead to disastrous consequences on the territory for both animals and humans. Agriculture and animal health parameters are strictly correlated factors and as such they should be considered when analysing pasture behaviours for a certain area with respect to animal diseases. A Geographical Information System (GIS) is a solid tool for the veterinary to manage data and find correlations with its location and spatial extension over time. GIS can lead to novel animal disease distribution models, thus helping in the interpretation of, e.g., an epidemic episode or a groundwater contamination. Contaminated or polluted areas have bad effects on herds insisting on that area and, as a side effect, on products and food connected with both animals and plants on the same area. Moreover, many misbehaviours in human-managed farms higher risks for human health. In mixed farms (i.e. where both animals and vegetable crops are managed) in fact, animal droppings are often used to manure vegetables, thus creating a potential risk for the diffusion of pathogenic micro-organisms polluting deep and superficial groundwater or producing even more serious problems.

In this paper we report about the project of using a GIS technology-based tool to monitor the land use of a large agricultural area, where high quality land products and animal based foods (such as milk production or cheese or meat); the idea is to verify whereas high concentration of animals related production, are land related with possible bacteria or problems in agricultural productions. The idea is to use GIS as potential prevention models for studying (i) farms as potential accumulators of pathogens, (ii) the environment (i.e. ground and water) as a collector of pathogens coming from herbs or farms and (iii) contaminated vegetable and crop production as a vehicle of infection for humans. We plan to use a tool implemented as a general purpose geographical information system with querying and spatial data management capabilities. Such a tool, called Geomedica, can be used easily and efficiently to design and implement ad hoc queries. A first set of queries performed over the preliminary dataset were able to validate our models and verify the correctness of our assumptions and to visualize results on a geographical map.