SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics. (arXiv:2211.08277v1 [cs.LG])

Predicting the evolution of diseases is challenging, especially when the data
availability is scarce and incomplete. The most popular tools for modelling and
predicting infectious disease epidemics are compartmental models. They stratify
the population into compartments according to health status and model the
dynamics of these compartments using dynamical systems. However, these
predefined systems may not capture the true dynamics of the epidemic due to the
complexity of the disease transmission and human interactions. In order to
overcome this drawback, …

arxiv embedding epidemics forecasting sparsity