What is Smart Healthcare System

With the global spreading of COVID-19, disease control has become a critical problem and an overwhelming challenge for our healthcare system. The decision-making of the control is mostly difficult because the disease is highly contagious, the policy-making procedures inappropriate, as well as the medical treatments and vaccines insufficient. Computational approaches such as mathematical modeling and simulation can assist to measure and prevent the pandemic. This chapter presents a set of SIR-based models for disease control in the context of COVID-19 with the empirical analysis based on the U.S. data. Data analysis and mathematical simulation results are illustrated to preview the progress of the outbreak and its future given different types of scenarios. The effect of interventions has been compared with that of the no-actions. The conclusion indicates that the public authorities can reduce the epidemic scale based on a strict strategy projected from the simulation results.