WPSII-7 New approach to modelling diseases: Temporal patterns of African Swine Fever in the Europen Union (2014–2017). (7th December 2018)

• Record Type: Journal Article
• Authors: Iglesias, I; Martinez, M; Linares, C; de la Torre, A; Perez, A
• Is Part Of: Journal of animal science. Volume 96(2018)Supplement 3
• Page Start: 517
• Page End: 518
• Publication Date: 2018-12-07
• Subjects: African-Swine-Fever -- Epidemiology -- Time-series-analysis; Livestock -- Periodicals; Livestock; Electronic journals; Periodicals; 636.005
• DOI: 10.1093/jas/sky404.1132
• Languages: English
• ISSNs: 0021-8812

Abstract

Abstract: The current situation of African Swine Fever (ASF) disease in the European Union (EU) represents a serious economic risk for the EU pig industry. Since its introduction in the EU in 2014 until now, the disease has been well controlled in domestic pigs and most cases (95%) have occurred in wild boar (WB). From the first notification in WB in Lithuania in 2014, the disease spread over long distance due to trade movements and also spread over short distance due to WB movements and contact transmission. It is necessary to anticipate at the disease in order to mitigate its growing expansion in WB, that represents a threat not only to nearby farm (especially those with low biosecurity) but also all commercial trades in the EU. Modeling techniques can help to explore and predict the ASF temporal pattern and therefore anticipate it focusing the surveillance program in high risk periods. In this study time-series methods were applied in order to identify the components of trend, seasonality, and autocorrelation of ASF notifications in EU by country in WB and domestic pigs separately during 2014–2017. To describe the trend, the monthly ASF notification was presented as a time-seriesgraph and tested using a bootstrapped Spearman test. An autoregressive integrated moving-average (ARIMA) process was fitted using IBM 21 software. The 2016 and, 2017 years of the study period had the highest monthly notification in both hosts. There was a large variability between years in both species. The more persistent temporal dependency in domestic pigs in July, August and September indicates that farms could benefit most from an increased frequency of sampling in the period leading up to and following this months. However, the results must be interpreted with caution, as there is a potential bias here related to the seasonal increase of commercial trade.