BackgroundThis study provides biochemical and molecular genetic characteristics of P. multocida isolated from dead saigas in 1988, 2010–2015 on the territory of the Republic of Kazakhstan.ResultsBacteriological samples taken from carcasses of saiga antelope during mortality events recorded in West Kazakhstan in both 2010 and 2011 and in Kostanay in 2012 and 2015 confirmed the presence of P. multocida, according to morphological and biochemical characterisation. Only in the event of 2015 was the agent proven to be the causative agent of the disease observed, haemorrhagic septicaemia. In the other mortality events it is not certain if the organism was a primary aetiology or an incidental finding as confirmatory pathological investigation was not undertaken. The implemented phylogenetic analysis of ribosomal RNA 16S gene allowed us to identify Pasteurella strains isolated in 2010–2015 as P. multocida subspecies multocida. Capsular typing by PCR showed that the studied strains isolated from dead saiga in 2010, 2011, 2012 and 2015 belonged to serotype B. MLST analysis showed that these strains of P. multocida are of the capsule type B and form one clonal grouping with isolates ST64, ST44, ST45, ST46, ST44, ST47 which isolated from cases of hemorrhagic septicemia of animals in Hungary, Burma, Sri Lanka, Pakistan and Spain. Sixteen virulence genes of the five strains of P. multocida, isolated from saigas were studied using multiplex PCR. ptfA, ompA, ompH, oma87, plpB, fimA, hsf-2, pfhA, exbB, tonB, hgbA, fur, nanB, nanH and pmHAS genes were detected in all strains. The toxA gene was not identified in the studied strains. The phylogenies of these isolates is compared across saiga populations and years and the 2015 isolate was compared to that of an isolate from a disease outbreak in 1988 and the findings suggest that these isolated bacteria are stable commensals, opportunistically pathogenic, being phylogenetically uniform with very little genetic variation notable over the last 4 decades.ConclusionIsolation, phenotypic and genetic characterization of the P. multocida isolates inform understanding of the epidemiology of infection in saigas and predict virulent potential of these opportunistic bacteria.

Peste des petits ruminants (PPR) is a viral transboundary disease seen in small ruminants, that causes significant damage to agriculture. This disease has not been previously registered in the Republic of Kazakhstan (RK). This paper presents an assessment of the susceptibility of the RK's territory to the spread of the disease in the event of its importation from infected countries. The negative binomial regression model that was trained on the PPR outbreaks in China, was used to rank municipal districts in the RK in terms of PPR spread risk. The outbreak count per administrative district was used as a risk indicator, while a number of socio-economic, landscape, and climatic factors were considered as explanatory variables. Summary road length, altitude, the density of small ruminants, the maximum green vegetation fraction, cattle density, and the Engel coefficient were the most significant factors. The model demonstrated a good performance in training data (R 2 = 0.69), and was transferred to the RK, suggesting a significantly lower susceptibility of this country to the spread of PPR. Hot spot analysis identified three clusters of districts at the highest risk, located in the western, eastern, and southern parts of Kazakhstan. As part of the study, a countrywide survey was conducted to collect data on the distribution of livestock populations, which resulted in the compilation of a complete geo-database of small ruminant holdings in the RK.The research results may be used to formulate a national strategy for preventing the importation and spread of PPR in Kazakhstan through targeted monitoring in high-risk areas.

Background and Aim: Infectious bovine keratoconjunctivitis (IBK; conjunctivitis) is a widespread eye disease in cattle. In 1960, the Gram-negative bacillus Moraxella bovis was discovered as one of IBK's etiological causal agents. This study aimed to clarify the epidemiological (epizootic) situation of cattle moraxellosis in the Republic of Kazakhstan. The study also maps the quantitative and qualitative indicators of the epidemiological (epizootic) process to develop more effective antiepizootic measures. Materials and Methods: We clinically examined both imported and local cattle species based on existing epidemiological (epizootological) units of economic entities in Kazakhstan. Then, we selected biomaterials for laboratory tests to screen for moraxellosis. Results: We clarified the epizootic situation for moraxellosis of cattle in Kazakhstan using data from the Meat Union of Kazakhstan, veterinary reports from the Veterinary Control and Surveillance Committee of the Ministry of Agriculture, Kazakhstan, and our results, obtained during visits to farms in the various regions of the republic. Conclusion: Based on the data of the conducted studies, we developed epizootic visualization maps with quantitative indicators of the cattle moraxellosis epizootic-transfer processes within various regions of Kazakhstan for 2019. The data obtained from studies of the properties of the isolated cultures compared with the characteristics of reference strains gave grounds to classify them as belonging to the Moraxella genus.

Peste des petits ruminants (PPR) is a viral transboundary disease of small ruminants that causes significant damage to agriculture. The disease has not been previously registered in the Republic of Kazakhstan (RK). This paper presents an assessment of the susceptibility of the RK territory to the spread of this disease in case of its importation from infected countries. Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models trained on the PPR outbreaks in China were used to rank municipal districts of the RK in terms of the risk of PPR spread. Spatial density of outbreaks was used as a risk indicator while a number of socio-economic, landscape and climatic indicators were considered as explanatory variables. The Exploratory Regression tool was used to reveal a best combination of independent variables based on specified thresholds of R-squared, variables' multicollinearity and residuals' normality and autocorrelation. The small ruminants' density, the maximum green vegetation fraction, the annual mean temperature, the road length and density as well as the cattle density were the most significant factors. Both OLS and GWR demonstrated nearly similar model performance providing a global adjusted R-squared of 0.61. Applied to the RK, the models show the greatest risk of PPR spread in the south-eastern and northern regions of the country, especially within Almaty, Zhambyl, Turkistan, West Kazakhstan and East Kazakhstan regions. As part of the study, a country-wise survey was carried out to collect data on the distribution of livestock population the RK, which resulted in compiling a complete geo-database of small ruminants' holdings in the country. The research results can be used to form a national strategy for the prevention of the importation and spread of PPR in Kazakhstan through targeted monitoring in high-risk areas.

Б а с р е д а к т о р Есполов Т.И., э.ғ.д, профессор, ҚР ҰҒА академигі жəне вице-президенті Р е д а к ц и я а л қ а с ы: