Jiaqi (Jackie) Chen

Jiaqi (Jackie) Chen

PhD student at the University of Hong Kong

Competition of SARS-CoV-2 Variants on the Pandemic Transmission Dynamics

Published in Chaos, Solitons and Fractals, 2023

✓ Published   First Author

Journal

Chaos, Solitons and Fractals    Impact Factor: 9.9    Rank #1 / 81 in Mathematical Physics    Citations: 30
📄 Read Paper (DOI: 10.1016/j.chaos.2023.113193)    Google Scholar

Abstract

This study presents a mathematical modeling framework for quantifying the competitive dynamics among COVID-19 variants during the pandemic. By formulating an ODE-based epidemiological model, we characterize how different SARS-CoV-2 variants compete for susceptible hosts via cross-immunity mechanisms, affecting both variant replacement timing and final epidemic size.

Key Contributions

  • Developed an ODE-based multi-variant competition model capturing cross-immunity and invasive behavior of new strains
  • Demonstrated significant predictive improvements over traditional deep learning time-series approaches
  • Predicted conditions for Delta resurgence and variant replacement dynamics in China

Technologies

Python   Mathematical Modeling (ODE)   Deep Learning   Epidemiological Simulation

Citation

Chen, J., Gu, C., Ruan, Z., & Tang, M. (2023). Competition of SARS-CoV-2 variants on the pandemic transmission dynamics. Chaos, Solitons and Fractals, 169, 113193. https://doi.org/10.1016/j.chaos.2023.113193

Recommended citation: Chen, J., Gu, C., Ruan, Z., & Tang, M. (2023). "Competition of SARS-CoV-2 Variants on the Pandemic Transmission Dynamics." Chaos, Solitons and Fractals, 169, 113193.
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