Integrated BLV surveillance in Kazakhstan, 2025: diagnostic complementarity and risk zoning.

Abstract

BACKGROUND: Bovine leukemia virus (BLV) is a cell-associated retrovirus that remains endemic in many cattle-producing countries. In the absence of effective vaccination, BLV control relies on sustained surveillance and accurate interpretation of serological and molecular diagnostic data. However, the systematic integration of multiple diagnostic layers with spatial analysis at the national level remains limited in endemic settings. METHODS: In 2025, a nationwide integrated surveillance of BLV was conducted in the Republic of Kazakhstan. A total of 3,650 serum samples were collected from 140 epidemiological units across 17 administrative regions. Cattle aged ≥24 months were examined using agar gel immunodiffusion (AGID) and enzyme-linked immunosorbent assay (ELISA) for serological screening, and polymerase chain reaction (PCR) for detection of proviral DNA. Partial sequencing was performed on selected PCR-positive samples for viral confirmation. Spatial analysis and territorial risk zoning were carried out using Geographic Information System (GIS)-based visualization to assess regional distribution patterns. RESULTS: BLV infection exhibited pronounced spatial heterogeneity across the country. Serological screening identified regions with varying levels of BLV circulation, while PCR confirmed proviral presence in seropositive animals and in a limited number of seronegative cases. Discrepancies between AGID, ELISA, and PCR results reflected differences in diagnostic sensitivity and infection stage rather than methodological inconsistency. Integration of serological, molecular, and spatial data enabled classification of territories into distinct risk zones and identification of localized clusters of increased BLV circulation. CONCLUSION: Integrated surveillance combining serological testing, molecular detection, and spatial analysis provides a robust framework for assessing BLV epidemiology in endemic countries. The 2025 data from Kazakhstan demonstrate that diagnostic complementarity is essential for accurate spatial risk zoning and epidemiological interpretation. This framework supports risk-based decision-making and is readily transferable to other BLV-endemic settings with heterogeneous production systems, potentially informing the development of targeted surveillance and control strategies.