  This study presents a novel approach at the intersection of genomic analysis
and artificial intelligence (AI) to predict viral mutations and assess the
risks of future pandemics. Through comprehensive genomic analysis, genetic
markers associated with increased virulence and transmissibility are
identified. Advanced machine learning algorithms are employed to analyze
genetic data and forecast viral mutations, taking into account factors such as
replication rates, host-pathogen interactions, and environmental influences.
The research also evaluates the risk of future pandemics by examining zoonotic
reservoirs, human-animal interfaces, and climate change impacts. AI-powered
risk assessment models provide insights into potential outbreak hotspots,
facilitating targeted surveillance and preventive measures. This research
offers a proactive approach to pandemic preparedness, enabling early
intervention and the development of effective containment strategies and
vaccines. The fusion of genomic analysis and AI enhances our ability to
mitigate the impact of infectious diseases on a global scale, emphasizing the
importance of proactive measures in safeguarding public health.
