Disease Transmission

Disease transmission research focuses on understanding and predicting the spread of infectious diseases to inform public health interventions. Current efforts leverage sophisticated computational models, including agent-based simulations, graph neural networks, and neural ordinary differential equations, to capture the complex interplay of individual behavior, environmental factors, and pathogen characteristics in disease spread. These models are increasingly incorporating high-resolution spatial data and individual heterogeneity to improve forecasting accuracy and assess the impact of various mitigation strategies. This work has significant implications for public health planning, resource allocation, and the development of effective disease control measures.