Estimating Parameters of Two-Level Individual-Level Models of the COVID-19 Epidemic Using Ensemble Learning Classifiers

The ongoing COVID-19 pandemic has led to a serious health crisis, and information obtained from disease transmission models fitted observed data is needed inform containment strategies. As the of virus varies city in different countries, we use two-level individual-level model analyze spatiotemporal SARS-CoV-2 spread. However, inference procedures such as Bayesian Markov chain Monte Carlo, which commonly used estimate parameters ILMs, are computationally expensive. In this study, trained ensemble learning classifiers ILMs show that can successfully capture among Wuhan 16 other cities Hubei province, China.