Maximising data to optimise animal disease early warning systems and risk assessment tools within Europe

Horigan, V. ; de Nardi, M. ; Crescio, M.I. ; Estrada-Peña, A. (Universidad de Zaragoza) ; Adkin, A. ; Maurella, C. ; Bertolini, S. ; Léger, A. ; Ru, G. ; Cook, C. ; Stark, K. ; Simons, R.R.L.

Resumen: Timely and reliable data and information availability and sharing is essential for early warning, prevention and control of transboundary diseases. While there are a growing number of global datasets capable of providing information for use in early warning systems and risk assessment (RA) tools, there are currently time-consuming data cleansing and harmonisation activities which need to be carried out before they can be reliably used and combined. Thus, using global datasets as they stand can lead to errors in RA parameterisation and results due to inherent biases in the data, e.g. missing disease prevalence data treated as a zero may inadvertently penalise those countries which do report disease outbreaks as opposed to those countries which are affected by a pathogen but do not report outbreak data. It is therefore of great importance that data are clearly provided and easy to understand and that data providers strive for greater harmonisation of database standards. In this paper the datasets utilised in the SPARE (’Spatial risk assessment framework for assessing exotic disease incursion and spread through Europe’) project are described and discussed in terms of key criteria: accessibility, availability, completeness, consistency and quality. It is evident that most databases exist as information portals and not exclusively for RA purposes. Another striking issue from this assessment is the need for enhanced data sharing specifically with regards to data on illegal seizures, arthropod vector/wildlife abundance, intra-country livestock movement and national animal disease surveillance. It is hoped that the outcomes of this work will promote discussion and exchange between data providers, including the development of standardised data exchange protocols. The transformation of datasets to a common format is a considerable challenge but recommendations could and should be made on the standardisation of datasets and reporting in order to achieve a unified approach across Europe.

Idioma: Inglés

DOI: 10.1016/j.mran.2019.02.003

Año: 2019

Publicado en: Microbial Risk Analysis 13 (2019), 100072 [11 pp]
ISSN: 2352-3522

Factor impacto JCR: 2.182 (2019)

Categ. JCR: FOOD SCIENCE & TECHNOLOGY rank: 66 / 139 = 0.475 (2019) - Q2 - T2
Categ. JCR: MICROBIOLOGY rank: 90 / 134 = 0.672 (2019) - Q3 - T3
Categ. JCR: ENVIRONMENTAL SCIENCES rank: 146 / 265 = 0.551 (2019) - Q3 - T2

Factor impacto SCIMAGO: 0.599 - Epidemiology (Q3) - Microbiology (medical) (Q3) - Infectious Diseases (Q3)

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Sanidad Animal (Dpto. Patología Animal)