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Modeling SARS-CoV-2 Infection Dynamics: Insights into Viral Clearance and Immune Synergy
Lele Fan1, Zhipeng Qiu2, Qi Deng3
1School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, 210094, People's Republic of China.
Bulletin of Mathematical Biology
|April 15, 2025
Summary
This study models the immune response to SARS-CoV-2, finding that antibodies, natural killer (NK) cells, and cytotoxic T lymphocytes (CTLs) synergize to reduce viral load. Enhancing B cell stimulation may be key for clearing the virus.
Area of Science:
- Immunology
- Mathematical Biology
- Virology
Background:
- Understanding SARS-CoV-2 interactions with the immune system is vital for COVID-19 treatments.
- Cellular and humoral immunity play key roles in viral clearance.
Purpose of the Study:
- To investigate SARS-CoV-2 infection dynamics using a mathematical model.
- To explore the impact of immune cells (NK, CTLs, B cells) and antibodies on viral load.
- To analyze complex immune response behaviors and potential multistability.
Main Methods:
- Formulation of a mathematical model for SARS-CoV-2, cellular, and humoral immunity.
- Model fitting using clinical data from eight COVID-19 patients.
- Numerical investigation of immune component impacts and bifurcation theory analysis.
Main Results:
- Synergy of NK cells, CTLs, and antibodies significantly reduces SARS-CoV-2 viral load.
- Antibodies are crucial; enhancing B cell stimulation may improve lung viral clearance.
- CTLs exhibit stronger and more sustained cytotoxic effects than NK cells.
Conclusions:
- Immune responses to SARS-CoV-2 can be complex, exhibiting multistability.
- Mathematical modeling provides insights into immune interactions and potential therapeutic targets.
- Findings suggest diversity in COVID-19 infection outcomes based on immune dynamics.
