Diagnostic gap analysis in animal health through combining public databases

Area of Science:

• Veterinary Medicine
• Epidemiology
• Public Health

Background:

• Infectious animal diseases pose significant threats to global food security and economies.
• Existing diagnostic technologies have limitations, creating gaps in disease control and surveillance.
• Effective animal health management requires comprehensive and accessible diagnostic tools.

Purpose of the Study:

• To develop and present a novel methodology for identifying diagnostic gaps in animal health.
• To pinpoint specific needs in livestock disease diagnosis.
• To inform targeted research and development for improved disease surveillance.

Main Methods:

• Integration of data from DISCONTOOLS (Diagnostics for Animals' List of Animal Health Diagnostics).
• Utilization of the World Animal Health Information System (OIE-WAHIS) data.
• Comparative analysis to identify discrepancies between available diagnostics and disease priorities.

Main Results:

• Significant diagnostic gaps were identified, particularly for high-priority infectious diseases in livestock.
• The methodology successfully highlighted areas requiring urgent attention in diagnostic development.
• Specific livestock diseases with critical unmet diagnostic needs were pinpointed.

Conclusions:

• The developed methodology provides a framework for assessing and addressing diagnostic needs in animal health.
• Prioritizing research and development based on identified gaps is crucial for effective disease control.
• Improving diagnostic capabilities is essential for safeguarding global food security and economic development.