Epidemiological Modelling

Epidemiological modeling uses mathematical and computational methods to understand and predict the spread of infectious diseases. Current research focuses on improving model accuracy and efficiency through advanced techniques like reinforcement learning to optimize control strategies, clustering algorithms to group countries based on social contact patterns, and neural processes to integrate data from multiple sources of varying fidelity. These advancements are crucial for informing public health interventions, resource allocation, and ultimately mitigating the impact of future outbreaks.