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Risk Factor Impact on African Swine Fever Transmission in Different Extensive Pig Production Settings in Serbia.

Jan PlutMelita HajdinjakJasna Prodanov RadulovićSiniša GrubačBiljana DjurdjevićMarina Štukelj
Published in: Viruses (2023)
The first case of ASF in a domestic pig population in Serbia was confirmed in 2019 in a backyard population. Today, outbreaks in wild boar and, more importantly, in domestic pigs are still occurring, although the government measures for ASF prevention are in place. The aim of this study was to determine critical risk factors and identify the possible reasons for ASF introduction into different extensive pig farms. The study was conducted on 26 extensive pig farms with confirmed ASF outbreaks, with data collected from beginning of 2020 to the end of 2022. Collected epidemiological data were divided into 21 main categories. After identifying specific values of variables as critical for ASF transmission, we identified nine important ASF transmission indicators as those variables for which at least 2/3 of the observed farms reported values critical for ASF transmission. Among them were type of holding, distance to hunting ground, farm/yard fencing, and home slaughtering; however, the hunting activity of pig holders, swill feeding, and feeding with mowed green mass were not included. We represented the data in the form of contingency tables to study associations between pairs of variables using Fisher's exact test. All pairs of variables in the group including type of holding, farm/yard fencing, domestic pig-wild boar contact, and hunting activity were significantly related; hunting activity of pig holders, holding pigs in backyards, unfenced yards, and domestic pig-wild boar contact were observed on the same farms. Free-range pig farming led to observed domestic pig-wild boar contact on all farms. The identified critical risk factors need to be strictly addressed to prevent the further spread of ASF to extensive farms and backyards in Serbia and elsewhere.
Keyphrases
  • risk factors
  • healthcare
  • genetic diversity
  • deep learning