SIGMA Animal Disease Data Model

Research output: Contribution to journalJournal articleResearch

Documents

  • Gabriele Zancanaro
  • Sotiria Eleni Antoniou
  • Marta Bedriova
  • Frank Boelaert
  • José Gonzales Rojas
  • Mario Monguidi
  • Helen Roberts
  • Nielsen, Søren Saxmose
  • Hans-Herman Thulke
Abstract The European Commission is routinely asking EFSA for scientific and technical support in the epidemiological analysis of animal disease outbreaks (i.e. African swine fever, lumpy skin disease and avian influenza) and to report or assess surveillance data (i.e. Echinococcus multilocularis and avian influenza). For this purpose, EFSA has over the last years carried out several data collections and gathered specific information on outbreaks, surveillance activities and concerned animal populations (i.e. poultry, domestic pigs, cattle and wildlife such as wild boar). EFSA aims to work together closely with Member States in order to (i) reduce the Member States? manual input of the data to be submitted to EFSA; (ii) avoid double reporting to EFSA; (iii) provide the Member States with tools to produce automatically their own draft national reports on animal health and surveillance in a protected environment to ensure data protection; (iv) increase the quality of the data received from the Member States; and (v) shorten the time to retrieve up-to-date data, relevant for risk assessment purposes. With this purpose, EFSA launched a project called SIGMA. It is important to highlight that the SIGMA ? Animal Disease Data Model (σ-ADM) focuses on data which are known to be already collected by several Member States under different legal frameworks and for different purposes. The version presented in this report, will be subject to modifications and updates derived from the feedback during the implementation phase.
Original languageEnglish
Article numbere05556
JournalEFSA Journal
Volume17
Issue number1
Number of pages60
ISSN1831-4732
DOIs
Publication statusPublished - 1 Jan 2019

    Research areas

  • SIGMA, data model, data collection, standardisation, population, surveillance

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