Background and Aim: Escherichia coli, a commensal intestine bacterium of vertebrates, is widely distributed in the environment and indicates the microbiological quality of food products in relation to coliforms. In addition, virulent strains, particularly E. coli O157:H7, cause outbreaks of toxic infections caused by consuming dairy products. Because food safety studies regarding E. coli have not been conducted in Central Asia, this research aimed to study the characteristics of contamination, microbiological and genotypic properties, and resistance to antimicrobial agents of E. coli strains that contaminate various types of commercialized cheeses originating from Kazakhstan. Materials and Methods: In retail outlets, 207 samples of three types of cheese produced by 22 industrial and eight small enterprises in the central, eastern, southern, and northern regions of Kazakhstan were selected in 2020–2023. E. coli contamination was examined using standard microbiological, mass spectrometric, and molecular genetic methods. The discodiffuse European Committee on Antimicrobial Susceptibility Testing method was used to test the resistance of the identified E. coli isolates (65/207; 31.4%) to 20 antibacterial drugs. The Shiga toxin-producing E. coli (VT1 and VT2) and E. coli O157:H7 (eae) genes were investigated in all E. coli isolates using multiplex polymerase chain reaction. Results: An average of 31.4% samples of commercial Kazakhstani cheeses of various types were found to be contaminated with E. coli in almost all geographical regions of Kazakhstan, regardless of the productivity of the dairy enterprises. Soft cheeses produced by small farms (80% of samples) packaged at the retail site (100%) were the most contaminated with E. coli. The microbiological index (colony-forming unit/g) was unsatisfactory and unsuitable in 6.2% of such cheese samples. For the first time in Central Asia, the enteropathogenic strain E. coli O157:H7 was detected in 0.5% of cheese samples. E. coli isolates from cheese samples were resistant to 65% of antibacterial drugs and contained resistance genes to β-lactams, sulfonamides, and quinolones groups. At the same time, 25% of the E. coli isolates were multi-resistant to three or more antimicrobial agents. Conclusion: The high level of contamination caused by multi-antibiotic resistant E. coli strains, including pathogenic pathogens, poses a risk to public health and highlights the need for further research on the monitoring and control of coliform enteropathogens in food products. Keywords: antibiotic resistance, Escherichia coli O157:H7, Kazakhstan cheese, microbial contamination.

Background and Aim: Manchurian quails are valued in commercial poultry farming for their early meat maturity, rapid generational turnover, and high egg-laying potential. However, concerns over antibiotic use in feed have heightened inter­est in sustainable alternatives such as phytobiotics. Despite evidence supporting phytogenic feed additives, limited studies have examined their effects in Manchurian quails under multiphase feeding regimens. This study evaluated the effects of phytobiotic-enriched, extruded feeds (BioFeed-P) across three feeding phases (“Starter,” “Grower,” and “Layer”) on growth performance, egg productivity, and product quality in Manchurian quails. Materials and Methods: A total of 1600 1-day-old quails were randomly allocated into experimental group (EG) and con­trol group (CG) at two commercial farms (JEBE; Zhailybayev Experimental Breeding Enterprise and ECO-KO; Ecological Cooperative Kazakhstan Organization)in Kazakhstan. EG received phytobiotic-enriched multiphase feeds, whereas CG was provided standard commercial diets. Growth rate, feed conversion ratio (FCR), survivability, and egg production were mea­sured over a 90-day period. Product quality was assessed by analyzing egg morphology, chemical composition, and mineral profiles. Statistical analyses included the Student’s t-test, correlation analysis, and determination of effect size. Results: Quails in EG showed significantly higher body weight gain (186.3 g vs. 135.3 g; relative gain 415.5% vs. 297.5%; p = 0.003, Cohen’s d = 1.12) and improved FCR (2.05 vs. 2.45; p = 0.001). Egg-laying intensity was greater in EG at both ECO-KO (64.4% vs. 41.3%; p = 0.004) and JEBE (69.0% vs. 40.0%; p = 0.003). Egg morphology showed modest changes: Heavier albumen, reduced shell weight, and lighter yolk pigmentation. Chemical analyses revealed slight decreases in pro­tein and fat fractions accompanied by minor increases in carbohydrate and ash content, while the mineral composition remained stable. Mortality was lower in EG (3.8% vs. 7.7%), with no adverse health effects. Conclusion: Phytobiotic-enriched multiphase feeds significantly enhance growth efficiency and reproductive output in Manchurian quails without compromising mineral egg quality. These findings support phytobiotics as sustainable alter­natives to antibiotics in commercial quail farming. Future research should include long-term reproductive assessments, economic cost–benefit analyses, and molecular studies to elucidate the underlying mechanisms. Keywords: egg production, feed additives, growth performance, phytobiotics, quail farming, sustainable poultry nutrition.

Background and Aim. Highly pathogenic avian influenza (HPAI) remains one of the most significant transboundary avian diseases, affecting affecting farmed, synanthropic, and wild bird populations. Migratory wild birds play a crucial role in the long-distance spread of avian influenza viruses across continents. The aim of this study is to develop an interactive geospatial dashboard for monitoring and assessing risk factors associated with HPAI along migration routes in Kazakhstan. Materials and Methods. Relevant spatial datasets related to the risk of avian influenza spread were integrated into an interactive geospatial dashboard. The analysis included bird migration and ringing data from EURING and the Institute of Zoology, georeferenced wild bird observations from the eBird platform (25,828 records representing 137 species), and outbreak data from the FAO EMPRES-i and WOAH WAHIS databases. Spatial analysis and data processing were performed using ArcGIS Pro, ArcGIS Online, and the R statistical environment, while species spatial distribution modeling was performed using the MaxEnt algorithm. Results. Through the integration and analysis of heterogeneous spatial datasets, an interactive geospatial dashboard was developed to assess the spatial distribution and potential spread of highly pathogenic avian influenza (HPAI) in Kazakhstan. The platform combines wild bird observation data from the eBird database, bird ringing and migration data, water body and wetland data, poultry density information, and officially recorded disease outbreaks. Interactive filtering tools allow data to be analyzed by geographic region, taxonomic group, and risk level. Spatial overlay analysis revealed overlap between areas of high wild bird activity and regions with intensive poultry farming, indicating potential ecological interfaces for virus transmission. The developed dashboard provides multi-layered visualization of epizootological data and supports rapid analysis of potential HPAI risk zones in Kazakhstan. Conclusion. The developed geospatial dashboard is an effective decision-support tool for veterinarysurveillance and epidemiological risk assessment. The integration of environmental and epidemiologicaldata enables the rapid identification of potential high-risk areas for the introduction and spread of highlypathogenic avian influenza, facilitating the development of evidence-based surveillance strategies.

Background and Aim. Highly pathogenic avian influenza (HPAI) remains a serious threat to industrial poultry farming and human health. The virus is highly variable and can be transmitted through the migratory flows of wild birds, which contribute to its widespread distribution. This study aimed to analyze the epidemiology of HPAI in Kazakhstan and assess the role of migratory birds therein. Materials and Methods. The study assessed data on outbreaks of HPAI in Kazakhstan for the period 2005 to 2024. Information on migratory bird species in Kazakhstan territories and their migration routes was obtained by the “Institute of Zoology”. The research applied classical methods of epidemiological analysis, statistical modeling of epizootics, and data visualization using ArcGIS Pro software. Results. Over the past 20 years (2005 to 2024), outbreaks of HPAI have been periodically recorded in Kazakhstan, with cases of infection in both domestic and wild birds. The pathogens mainly comprised viruses of the H5N1, H5N8, and other H5 strains. Wild migratory birds played the main role in the emergence and spread of HPAI. The territory of Kazakhstan contained the convergence point of two of their most important migration routes: the Central Asian-Indian and West Asian-African routes. A total of 489 bird species has been registered in Kazakhstan, most of which are seasonal migrants flying through the country; accordingly, they have a significant impact on the epizootic process of HPAI. Conclusion. Analysis of epizootiological data showed that the dates and locations of HPAI outbreaks directly correlated with the stages and routes of the seasonal migration of migratory birds. Predictive modeling of virus spread showed that the northern and western regions of the country, where most of the country’s poultry farms are located, were at the highest risk.

Highly pathogenic avian influenza (HPAI) is a transboundary disease of birds with zoonotic potential. Since 2021, H5 HPAI virus variants have spread globally, with migratory waterfowl playing a key role in transcontinental dissemination. Kazakhstan lies at the intersection of major flyways, creating a persistent risk of virus introduction into domestic poultry. While HPAI risk in wild birds has been explored in Kazakhstan, the spatial risk for poultry has remained underassessed. Here, we present a risk map for HPAI in poultry across 174 administrative districts of Kazakhstan, using a multi-criteria decision analysis (TOPSIS) that integrates five quantitative risk indicators that relate to wild bird habitat, virus survival in the environment and poultry farm census. The obtained district-level risk index agreed well with historical outbreak data (2005–2025), with an area under the receiver operating characteristic (ROC) curve of 0.899 (95% CI: 0.846–0.952). Most districts (56%) were at negligible risk, whereas medium- and high-risk clusters occurred in the north, central, and southern regions, and near the Caspian Sea. These findings provide an operational, spatially explicit tool for targeting surveillance and biosecurity measures to high-risk areas, ultimately helping to mitigate the impact of one of the most devastating transboundary poultry diseases in Central Asia.