Monitoring Serially Correlated Data by New CUSUM Chart (Case Study: Numbers of Patients with Covid-۱۹)

Statistical process control charts are important for quality control and management in manufacturing industries, disease monitoring and many other applications. SPC charts usually are designed for cases when process observations are independent at different observation times. However, serial data correlation almost always exists in sequential data. Thus, it is important to develop control charts specially for monitoring serially correlated data. On the other hand, one of the most important cases today is the Covid-۱۹ epidemic, and it has been proven that any infected person can infect other people whose symptoms appear a few days later. In this paper, we use the new CUSUM chart to monitor the number of patients with Covid-۱۹, which runs for three countries include Iran, Japan and Italy. The results displayed separately for each country and explained with appropriate tools. Meanwhile, a sensitivity analysis on important factors is performed and similar results are obtained.

Keywords:

Data correlation , CUSUM chart , Process monitoring , Covid-۱۹ , Patients number.