Construction and Simulation Analysis of Epidemic Propagation Model Based on COVID-19 Characteristics

Area of Science:

• Epidemiology
• Mathematical Modeling
• Infectious Disease Dynamics

Background:

• COVID-19 (Corona Virus Disease of 2019) presents complex propagation dynamics.
• Classical epidemic models may not fully capture unique disease characteristics.

Purpose of the Study:

• To propose and validate the SEAIHR epidemic propagation model for COVID-19.
• To enhance prediction accuracy by incorporating specific disease states.

Main Methods:

• Developed the SEAIHR model, introducing hospitalization, recessive healing, and home morbidity states.
• Analyzed COVID-19 propagation characteristics and prevention measures.
• Conducted comparative simulations using real epidemic data and varying parameters across different stages.

Main Results:

• The SEAIHR model demonstrated superior fitting and prediction accuracy.
• Achieved 34.4-72.8% lower fitting error compared to classical models in early and middle epidemic stages.

Conclusions:

• The SEAIHR model offers a more accurate representation of COVID-19 transmission.
• The model's enhanced features improve understanding and prediction of epidemic spread.