Spread Trajectory

Spread trajectory analysis focuses on understanding and predicting the patterns of how phenomena, such as diseases or invasive species, disseminate over time and space. Current research employs diverse computational methods, including neural networks (like Physics-Informed Neural Networks and parameterized architectures), attributed network embeddings, and differential equation models (e.g., SIR models and their variants), to analyze spread patterns and identify influential factors. These analyses are crucial for informing public health interventions, resource allocation, and effective control strategies in various domains, from pandemic management to invasive species control. The ultimate goal is to develop more accurate predictive models that enable proactive and targeted responses.