Simulation Prediction and Control Strategy of COVID-19 Dynamic Contact Network in USA and Various States -- Based on Effective Regeneration Number and Improved Discrete SEIQDHR Model

ABSTRACT

Purpose: Based on the latest characteristics of the transmission mechanism of the COVID-19 epidemic in the United States, this article improves the classic dynamics model of the spread of infectious diseases, simulates and predicts the future trend of the COVID-19 epidemic in the United States and various states. According to the computer program of COVID-19 dynamic contact network, the results provide effective control strategies for the future epidemic prevention work of the United States. Method: The SEIR model is improved by the latest effective reproduction number of the COVID-19 epidemic in the United States, and an improved discrete SEIQDHR model is established for the spread of the COVID-19 epidemic in the United States and various states. MATLAB software is used to perform least square fitting of key parameters, and the computer simulation process of COVID-19 dynamic contact network is solved dynamically. Results: The improved discrete SEIQDHR model is reliable in the analysis of the spread of infectious diseases. The model well simulates the current dynamic contact network of the COVID-19 epidemic in the United States. The results of computer program show that mid-to-late November 2020 is the period with the largest number of new diagnoses before the end of the epidemic in the United States. In a long period of time in the future, the cumulative number of confirmed cases in the United States and states will continue to show a clear upward trend. The cumulative number of confirmed cases of the COVID-19 epidemic in the United States will reach its peak in early December 2021, which is about 37.11 million;the cumulative number of confirmed cases in Texas will reach its peak on March 15, 2021, about 3.21 million. Controlling the source of infection, blocking the route of transmission and strengthening the tracking and isolation are still effective measures to prevent and control the epidemic.