An Epidemic Graph's Modeling Application to the COVID‐19 Outbreak: Concepts, Methodologies, Tools and Applications

The furious disease named COVID-19 is an outbreak in the current scenario. To control the spreading of this disease, new models were developed which utilized established methodologies to analyze how different containment strategies will influence the spread of the virus. It presents a novel machine learning approach that can estimate any epidemiological model's parameters based on two types of information: either static or dynamic. It primarily utilizes the Graph model using deep learning approaches and Long-term memories (LSTMs) to obtain mobility data's spatial and temporal properties of SIR and SIRD models. It runs and simulates using data on the Italian COVID dynamics and compares the model predictions to previously observed epidemics.