Abstract
Infectious disease surveillance is critical for monitoring and controlling the spread of pathogens. Recent advances in bioinformatics have significantly enhanced the ability to track infectious diseases, identify emerging pathogens, and predict outbreaks. Bioinformatics tools and techniques, such as genomic sequencing, metagenomics, and machine learning, have been integrated into surveillance systems to provide real-time data on disease dynamics. This article explores the role of bioinformatics in infectious disease surveillance, focusing on the application of genomic and computational approaches for early detection, epidemiological modeling, and outbreak prediction.
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