DIGITAL MONITORING TECHNOLOGIES IN VETERINARY ZOOLOGY: OPPORTUNITIES FOR DETECTING AND FORECASTING THE SPREAD OF PARASITES

The spread of parasites of veterinary importance is increasingly shaped by climate change, intensified animal movement and anthelmintic resistance, which challenges conventional surveillance based on sporadic laboratory examinations. This article reviews digital monitoring technologies applicable to veterinary zoology and evaluates their potential for detecting and forecasting parasite distribution. Four technology domains were analysed: automated and artificial intelligence (AI)-assisted diagnostics, geographic information systems (GIS) and remote sensing, mechanistic and machine-learning forecasting models, and precision livestock farming sensors. The results show that image-based automated egg counting achieves agreement with conventional methods sufficient for field decision-making, that satellite-derived temperature and vegetation indices reliably explain the spatial distribution of Fasciola hepatica and ixodid ticks, and that climate-driven simulation models can anticipate seasonal infection peaks. A four-layer integrated digital surveillance framework is proposed for Uzbekistan, and the main barriers – data scarcity, validation, connectivity and cost – are discussed.