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Rabies is a fatal zoonotic disease that remains endemic in Kazakhstan despite the implementation of annual vaccination campaigns. Using data collected over a 10-year time period, the objective of this study was to provide updated information on the epidemiological situation of the disease in the country, and quantitative data on the species-specific spatial distribution of rabies and on the epidemiological features associated with that clustering. Five significant (p

African swine fever (ASF) is an infectious disease that affects both domestic pigs (DPs) and wild boar (WB). The WB population plays an important role in the spread of ASF as the WB acts as a natural reservoir of the virus and transmits it to other susceptible wild and domestic pigs. Our study was aimed at revealing the areas with a high concentration of the WB population, and their potential relationships with the grouping of ASF cases in WB during the course of the ASF spread in the Russian Federation (2007–2022). We collected the annual data on WB numbers by municipalities within the regions of the most intensive ASF spread. We then conducted spatiotemporal analysis to identify clustering areas of ASF cases and compare them with the territories with a high density of WB population. We found that some of the territories with elevated ASF incidence in WB demonstrated spatial and temporal coincidence with the areas with a high WB population density. We also visualized the zones (“emerging hot spots”) with a statistically significant rise in the WB population density in recent years, which may be treated as areas of paramount importance for the application of surveillance measures and WB population control.

African swine fever (ASF) is an incurable viral disease of domestic and wild pigs. A large-scale spread of ASF began in Eurasia in 2007 and has affected territories from Belgium to the Far East, occurring as both local- and regional-level epidemics. In 2020, a massive ASF epidemic emerged in the southeastern region of European Russia in the Samara Oblast and included 41 outbreaks of ASF in domestic pigs and 40 cases in wild boar. The Samara Oblast is characterized by a relatively low density of wild boar (0.04–0.05 head/km2) and domestic pigs (1.1–1.3 head/km2), with a high prevalence of small-scale productions (household farms). This study aims to understand the driving forces of the disease and perform a risk assessment for this region using complex epidemiological analyses. The socioeconomic and environmental factors of the ASF outbreak were explored using Generalized Linear Logistic Regression, where ASF infection status of the Samara Oblast districts was treated as a response variable. Presence of the virus in a district was found to be most significantly (p < 0.05) associated with the importation of live pigs from ASF-affected regions of Russia (OR = 371.52; 95% CI: 1.58–87290.57), less significantly (p < 0.1) associated with the density of smallholder farms (OR = 2.94; 0.82–10.59), volume of pork products' importation from ASF-affected regions of Russia (OR = 1.01; 1.00–1.02), summary pig population (OR = 1.01; 0.99–1.02), and insignificantly (p > 0.1) associated with presence of a common border with an ASF-affected region (OR = 89.2; 0.07–11208.64). No associations were found with the densities of pig and wild boar populations. The colocation analysis revealed no significant concentration of outbreaks in domestic pigs near cases in wild boar or vice versa. These results suggest that outbreaks notified in low biosecurity household farms were mainly associated with the transportation and trade of pigs and pork products from ASF-affected regions of Russia. The findings underline the importance of taking into account animal transportation data while conducting future studies to develop a risk map for the region and the rest of European Russia.

African swine fever (ASF) is an emerging viral contagious disease affecting domestic pigs (DP) and wild boar (WB). ASF causes significant economic damage to the pig industry worldwide due to nearly 100% mortality and the absence of medical treatments. Since 2019, an intensive spread of ASF has been observed in the Russian Far East region. This spread raises concerns for epidemiologists and ecologists given the potential threat to the WB population, which is an essential member of the region's wild ungulates and provides a notable share of food resources for predatory species. This study aims to determine the genotype of ASF virus circulating in the region, reveal the spatio-temporal patterns of the ASF outbreaks' emergence, and assess the potential reduction of the regional fauna because of expected depopulation of WB. The first historical case of ASF in the study region was caused by an African swine fever virus (ASFV) isolated from DPs and belonging to Genotype 2, CVR1; IGR-2 (TRS +). Sequencing results showed no significant differences among ASFV strains currently circulating in the Russian Federation, Europe, and China. The spatiotemporal analysis with the space-time permutations model demonstrated the presence of six statistically significant clusters of ASF outbreaks with three clusters in DPs and one cluster in WBs. DP outbreaks prevail in the north-west regions of the study area, while northern regions demonstrate a mixture of DP and WB outbreaks. Colocation analysis did not reveal a statistically significant pattern of grouping of one category of outbreaks around the others. The possible damage to the region's fauna was assessed by modeling the total body mass of wild ungulates before and after the wild boars' depopulation, considering a threshold density of WB population of 0.025 head/km2, according to the currently in force National Plan on the ASF Eradication in Russia. The results suggest the total mass of ungulates of the entire study region will likely decrease by 8.4% (95% CI: 4.1–13.0%), while it may decrease by 33.6% (19.3–46.1%) in the Primorsky Krai, thereby posing an undeniable threat to the predatory species of the region.

Classical swine fever (CSF) is considered one of the most important diseases of swine because of the far-reaching economic impact the disease causes to affected countries and regions. The state of Mato Grosso (MT) is part of Brazil's CSF-free zone. CSF status is uncertain in some of MT's neighboring States and countries, which has resulted in the perception that MT is at high risk for the disease. However, the risk for CSF introduction into MT has not been previously assessed. Here, we estimated that the risk for CSF introduction into the MT is highly heterogeneous. The risk associated with shipment of commercial pigs was concentrated in specific municipalities with intense commercial pig production, whereas the risk associated with movement of wild boars was clustered in certain municipalities located close to the state's borders, mostly in northern and southwestern MT. Considering the two pathways of possible introduction assessed here, these results demonstrate the importance of using alternative strategies for surveillance that target different routes and account for different likelihoods of introduction. These results will help to design, implement, and monitor surveillance activities for sustaining the CSF-free status of MT at times when Brazil plans to expand the recognition of disease-free status for other regions in the country.

The Yamal Peninsula in the Russian Federation experienced a massive outbreak of anthrax in reindeer (Rangifer tarandus) in July–August 2016, with 2,650 (6.46% of the total susceptible population) animals infected, of which 2,350 died (case fatality rate of 88.67%). In our study, we analyzed climatic and epidemiological factors that could have triggered the outbreak. The cancelation of reindeer vaccination against anthrax in 2007 resulted in an increase in population susceptibility. In response to the outbreak, total vaccination of all susceptible animals was resumed. To assess the vaccination effectiveness, we tested 913 samples of blood serum taken from vaccinated reindeer using an antigenic erythrocyte diagnostic kit to detect specific anti-anthrax antibodies via an indirect hemagglutination assay (IHA) 9 months after vaccination. We found that 814 samples had sufficiently high levels of anti-anthrax antibodies to indicate a protection level of 89% (95% confidence interval: 87–91%) of the whole reindeer population. Abnormally high ambient temperature in the summer of 2016 contributed to the thawing of permafrost and viable Bacillus anthracis spores could have become exposed to the surface; the monthly average air temperatures in June, July, and August 2016 were 20–100% higher than those of the previous 30-year period, while the maximum air temperatures were 16–75% higher. Using the projected climate data for 2081–2100 according to the “worst case” RCP8.5 scenario, we demonstrated that the yearly air temperature may average above 0°C across the entire Yamal Peninsula, while the yearly number of days with a mean temperature above 0°C may rise by 49 ± 6 days, which would provide conditions for reactivation of soil anthrax reservoirs. Our results showed that the outbreak of anthrax occurred under conditions of a significant increase in air temperature in the study area, underlined the importance of vaccination for controlling the epidemic process, and demonstrated the effectiveness of monitoring studies using the IHA diagnostic kit for detecting erythrocyte anthrax antigens.

Leptospirosis is a re-emerging zoonotic infectious disease caused by pathogenic bacteria of the genus Leptospira. Regional differences in the disease manifestation and the role of ecological factors, specifically in regions with a subarctic and arctic climate, remain poorly understood. We here explored environmental and socio-economic features associated with leptospirosis cases in livestock animals in the Russian Arctic during 2000–2019. Spatial analysis suggested that the locations of the majority of 808 cases were in “boreal” or “polar” climate regions, with “cropland,” “forest,” “shrubland,” or “settlements” land-cover type, with a predominance of “Polar Moist Cropland on Plain” ecosystem. The cases demonstrated seasonality, with peaks in March, June, and August, corresponding to the livestock pasturing practices. We applied the Forest-based Classification and Regression algorithm to explore the relationships between the cumulative leptospirosis incidence per unit area by municipal districts (G-rate) and a number of socio-economic, landscape, and climatic factors. The model demonstrated satisfactory performance in explaining the observed disease distribution (R2 = 0.82, p < 0.01), with human population density, livestock units density, the proportion of crop area, and budgetary investments into agriculture per unit area being the most influential socio-economic variables. Climatic factors demonstrated a significantly weaker influence, with nearly similar contributions of mean yearly precipitation and air temperature and number of days with above-zero temperatures. Using a projected climate by 2100 according to the RCP8.5 scenario, we predict a climate-related rise of expected disease incidence across most of the study area, with an up to 4.4-fold increase in the G-rate. These results demonstrated the predominant influence of the population and agricultural production factors on the observed increase in leptospirosis cases in livestock animals in the Russian Arctic. These findings may contribute to improvement in the regional system of anti-leptospirosis measures and may be used for further studies of livestock leptospirosis epidemiology at a finer scale.

African swine fever (ASF) is a disease of swine that is endemic to some African countries and that has rapidly spread since 2007 through many regions of Asia and Europe, becoming endemic in some areas of those continents. Since there is neither vaccine nor treatment for ASF, prevention is an important action to avoid the economic losses that this disease can impose on a country. Although the Republic of Kazakhstan has remained free from the disease, some of its neighbors have become ASF-infected, raising concerns about the potential introduction of the disease into the country. Here, we have identified clusters of districts in Kazakhstan at highest risk for ASF introduction. Questionnaires were administered, and districts were visited to collect and document, for the first time, at the district level, the distribution of swine operations and population in Kazakhstan. A snowball sampling approach was used to identify ASF experts worldwide, and a conjoint analysis model was used to elicit their opinion in relation to the extent at which relevant epidemiological factors influence the risk for ASF introduction into disease-free regions. The resulting model was validated using data from the Russian Federation and Mongolia. Finally, the validated model was used to rank and categorize Kazakhstani districts in terms of the risk for serving as the point of entry for ASF into the country, and clusters of districts at highest risk of introduction were identified using the normal model of the spatial scan statistic. Results here will help to allocate resources for surveillance and prevention activities aimed at early detecting a hypothetical ASF introduction into Kazakhstan, ultimately helping to protect the sanitary status of the country.