Known and Unknown Transboundary Infectious Diseases as Hybrid Threats

Area of Science:

• Microbiology
• Biosecurity
• National Security

Background:

• Microorganisms are increasingly recognized as hybrid threats due to their pathogenicity, transmissibility, and potential for genetic manipulation.
• These agents can evade current detection, attribution, and response capabilities, posing significant risks to national health, trade, and security.
• Existing biosurveillance methods are limited in scope and struggle to address the complexity of novel microbial threats.

Purpose of the Study:

• To discuss the use of microorganisms as hybrid threats.
• To propose a framework for enhanced horizon scanning and risk assessment of microbial hybrid threats.
• To advocate for the transition towards autonomous biosurveillance systems.

Main Methods:

• Conceptual framework development for microbial hybrid threat risk assessment.
• Discussion of machine learning (ML) and artificial intelligence (AI) applications in autonomous biosurveillance.
• Integration of diverse data streams for comprehensive threat analysis.

Main Results:

• Autonomous biosurveillance systems can process vast data streams beyond human cognitive limits.
• ML and AI algorithms can contextualize threat information for strategic and tactical stakeholders.
• A quantitative risk estimation approach is essential for societal preparedness and resilience.

Conclusions:

• Microbial hybrid threats necessitate advanced, autonomous biosurveillance capabilities.
• AI and ML are key enablers for effective detection, attribution, and response to these threats.
• Societal awareness, preparedness, and resilience are paramount in mitigating the risks posed by microbial hybrid threats.