Monitoring Serially Correlated Data by Two CUSUM Charts (Case Study: Numbers of Patients with Covid-19)

Statistical process control charts are utilized in many industries, including manufacturing, environmental monitoring and improvement, disease surveillance, and others. The use of statistical process control charts is common for independent process observations at different times. However, in the case of sequential data, correlation between the data is typically present. Therefore, the creation of control charts specifically for monitoring serially correlated data is essential. The Covid-19 epidemic is a severe global issue, with evidence indicating that infected individuals can transmit the virus to others, whose symptoms may appear several days later. This study aims to monitor the condition of Covid-19 patients over a specific period time using serial data. Two new CUSUM charts are used to track the number of Covid-19 patients in Iran, Japan, and Italy, with separate results presented and explained for each country. Additionally, a sensitivity analysis is conducted on key factors, yielding similar results, and the two control charts are compared.