Abstract—The European Commission’s Animal Health Strategy for the period 2007-2013 is outlined in . The work plan is structured into four macro-actions. Among them, we report the action oriented to “Better prevention, surveillance and crisis preparedness” because prevention and control are keywords of the present study. In detail, this article proposes an algorithm (CHECK) and a supporting database to control the diffusion of animal diseases. The working procedure we imagine works as follows. Downstream of the outbreak of cases of livestock disease, the farms which might be infected are detected by running the CHECK algorithm. Then a campaign of veterinary visits restricted to those farms has to be started and when the circumstances would demand it, it will be necessary to have recourse to specific studies suitable to identify which farms are to be culled in order to ward off the danger of the ignition of a real health emergency. Unfortunately, the correctness of the prediction of this latter category of studies is subordinated to the degree of adherence of their input data to the reality. In the paper we will clarify why the results returned by the method we are going to propose are highly reliable and, hence, they are suitable as input data to the existing culling strategies. Given the relevance of the organization of the supporting database, as the preliminary step to reach an effective and efficient solution to the problem of the management of situations of crisis, in the present paper we will discuss and compare alternative solutions all feasible with the software products today available. The arguments we will adduce are quite general, therefore they are of interest for all medical or computer scientists who are concerned with building medical databases for similar purposes.
Index Terms— animal health, contagion, epidemic, prevention, animal movements, parking area, database, moving points databases, SQL
Cite: Paolino Di Felice and Americo Falcone, "An Algorithm and a Database: Two Conceptual Tools to Control the Diffusion of Animal Diseases," Journal of Advances in Information Technology, Vol. 4, No. 1, pp. 40-50, February, 2013.doi:10.4304/jait.4.1.40-50
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