Author(s)

Shijun Gao¹, Xinzhe Yao², Hua He^1*

¹School of Science, Hebei University of Technology, Tianjin, China.
²School of Statistics and Data Science, Nankai University, Tianjin, China.

Infectious diseases have always been critical factors affecting human life, health, and social stability throughout history. The recurrent epidemics of infectious diseases have caused enormous disasters for human survival and national well-being. Establishing mathematical models to describe the transmission process of infectious diseases, analyze the variation patterns of infected individuals, and predict disease outbreak timing is significant for providing a decision-making basis to prevent the spread of infectious diseases. The use of dynamic models specific to infectious diseases offers unique advantages in addressing these issues. In this paper, a two-stage infectious disease dynamics model with a latent period and asymptomatic infection is established to model the transmission of highly infectious pathogens in a population. Utilizing epidemic data from Shanghai spanning February 8, 2022, to July 1, 2022, the model is numerically simulated, and the basic reproduction number $R_0$ for the two stages is calculated using the next generation matrix method. Studies indicate that timely enhancements in epidemic control measures can significantly reduce the number of confirmed cases in hospitals, decrease the peak number of infections, and hasten the arrival of the epidemic’s inflection point.

Epidemic Dynamics Model, Numerical Simulation

Gao, S. , Yao, X. and He, H. (2025) Improved Two-Stage Epidemic Dynamics Model. Journal of Applied Mathematics and Physics, 13, 1665-1682. doi: 10.4236/jamp.2025.135092.