Diagnostic gap analysis in animal health through combining public databases

Abstract

Abstract The burden of infectious diseases in animals, particularly in livestock, significantly impacts global food security and economic development. Despite advancements in diagnostic technologies, substantial gaps remain that hinder effective disease control and surveillance. This study presents a new methodology for identifying gaps in animal health diagnosis by integrating data from DISCONTOOLS, the Diagnostics for Animals’ List of Animal Health Diagnostics, and the World Animal Health Information System. Our analysis highlights significant diagnostic needs, particularly for high-priority infectious diseases in livestock. The findings aim to guide research and development efforts to improve disease surveillance and control.