ABSTRACT
Objective To solve the data difference between COVID-19 confirmed cases and actual number of COVID-19 infections, a new model is proposed to predict the spread of the disease. The data difference has been mainly caused by insufficient understanding in the early stage of transmission, limited detection capabilities and the long incubation period. Methods The historical data of the number of confirmed cases are analyzed based on Window-Time. A Long Short-Term Memory (LSTM) network model is combined with the Window-Time strategy to analyze and predict the actual number of infections according to data published of various regions in the world. Results The LSTM network model with Window-Time strategy has higher accuracy than other models. Tuning the width of the Window-Time to the width of 5, the prediction result shows that it is closest to the real actual number of infections, which is consistent with the incubation period of COVID-19 generally known as 3-7 days. Conclusion This method provides a reference for the analysis of the transmission rate of COVID-19 and the incubation period of the epidemic. © 2021, Publication Centre of Anhui Medical University. All rights reserved.