Abstract
African swine fever (ASF) is a transboundary viral disease that affects both domestic pigs and wild boar, causing enormous damage to the pig production. Numerous studies are devoted to elucidating the role of domestic and wild pigs in ASF outbreaks. The identification of the risk factors contributing to the spread of disease in previously unaffected regions is of special interest. We conducted a retrospective analysis of sporadic ASF outbreaks in the Nizhny Novgorod region of the Russian Federation from 2011 to 2022 among both domestic pig and wild boar populations. Methods of spatiotemporal cluster analysis, mathematical modeling with logistic and negative binomial regressions, as well as the cross-correlation analysis of time series, were used to identify the most significant factors associated with the ASF outbreaks' presence and intensity. Regression analysis did not reveal a statistically significant correlation between ASF outbreaks in wild boar and their population density over the entire study period. However, the spatial and temporal coincidence between outbreaks and increased wild boar density was observed at the beginning of the ASF epidemic in the region. We identified the significant environmental and sociodemographic factors contributing to the spread of ASF in both domestic pig and wild boar populations. The number of small-scale farms (backyards) and summary road length were determined as the main factors contributing to the spread of ASF among domestic pigs in the Nizhny Novgorod region. The regression model for ASF outbreaks in the wild boar population revealed the presence of water bodies, number of hunting farms, and the occurrence of ASF outbreaks in the domestic pig population to be the main explanatory factors. A statistically significant coincidence was identified between the monthly volume of pork products imported to the region from the rest of Russia and the occurrence of ASF outbreaks in both domestic and wild populations. Thus, the identified spatiotemporal patterns may be useful to determine areas with an elevated risk of ASF outbreaks emergence for better resource management, disease control, and prevention. The importance of intensified monitoring and control measures in the pig products supply chain is strongly needed. The obtained models can be applied not only by the veterinary service of the Nizhny Novgorod region but to other regions with similar environmental and sociodemographic conditions.