Francesco Sgarangella
Azienda Tutela della Salute (ATS), ASSL of Sassari (Sardinia), Animal Health Service
Title: Official control activities under the African swine fever (asf) extraordinary plan in Sardinia: monitoring of non-compliance of the 2015 standard criteria
Biography
Biography: Francesco Sgarangella
Abstract
Statement of the Problem:
The goal of the 2015-2017 Extraordinary Program (EP), approved by the European Commission, had the objective of eradicating African swine fever from the regional territory. According to risk maps elaborated by the Regional Epidemiological Observatory, in 2015, the EP presupposed an official check on pig farms regarding: registrations, biosecurity and animal welfare measures. The aim of this work is to illustrate the results of non-compliance evidenced during official controls under EP, classify their typology, connect them with different territorial risks in order to define intervention priorities and to reduce the risk of spread of ASF virus .
Methodology & Theoretical Orientation:
Data were entered weekly on the Animal Health Service information system (E-VET), a computerized database based on pig farm registry. The use of farm codes and geographic coordinates has allowed us to categorize non-conformities and contextualize them across the regional territory through multi-stratum maps (GIS technology).
Findings:
Out of 2,950 controlled farms, 1864 non-conformities were detected; 44.6% were about biosecurity, 26% regarding pigs registration, the remaining part of non-compliance concerned reproductive parameters.
Conclusion & Significance:
The described model, based on the employment of a local software implemented with the non-compliance data ascertained during official monitoring activities and the subsequent data mapping on thematic maps (GIS), highlighted the major criticalities on pig farm registry management and biosecurity measures, particularly in wild pigs ASF infected areas. By associating the different types of non-conformities to the territorial context, which is diverse from an epidemiological point of view, it was possible to model the timing of official controls during the 2016 activity, prioritizing official controls to high risk farms.