Development of a Dashboard for Monitoring and Risk Assessment of Highly Pathogenic Avian Influenza in Kazakhstan

Abstract

Abstract

Background and Aim.Highly pathogenic avian influenza (HPAI) remains one of the most significant transboundary avian diseases, affecting both farmed and synanthropic and wild bird populations worldwide. 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 (Euring 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.By integrating and analyzing 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 links virus transmission. The developed dashboard provides multi-layered visualization of epizootological data and enables rapid analysis of potential HPAI risk zones in Kazakhstan.

Conclusion.The developed geospatial dashboard is an effective decision-support tool for veterinary surveillance and epidemiological risk assessment. The integration of environmental and epidemiological data enables the rapid identification of potential high-risk areas for the introduction and spread of highly pathogenic avian influenza, facilitating the development of evidence-based surveillance strategies.