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Modeling and analysis of COVID-19 based on a time delay dynamic model
Cong Yang1, Yali Yang1, Zhiwei Li1
1Department of Basic Sciences, Air Force Engineering University, Xioan 710051, China.
Mathematical Biosciences and Engineering : MBE
|February 2, 2021
Summary
A new infectious disease model with time delay accurately describes COVID-19 transmission dynamics. Early detection and isolation are crucial for epidemic control, as demonstrated by simulations in Wuhan and Beijing.
Area of Science:
- Epidemiology
- Mathematical Biology
- Infectious Disease Modeling
Background:
- The novel coronavirus pneumonia (COVID-19) emerged in late 2019, exhibiting high contagiousness and significant global impact.
- Existing infectious disease models struggle to accurately capture COVID-19 transmission due to its unique characteristics, including high infectivity during incubation.
- The absence of specific antiviral drugs necessitates a scientific understanding of epidemic development for effective prevention and control.
Purpose of the Study:
- To develop and validate a novel infectious disease model incorporating time delays to better represent COVID-19 transmission.
- To simulate the epidemic's trajectory using real-time data and analyze the effectiveness of public health interventions.
- To compare the epidemic's severity and control strategies in Beijing and Wuhan.
Main Methods:
- An enhanced infectious disease model was formulated, integrating time delays to account for viral incubation and treatment periods.
- Numerical simulation and parameter inversion techniques were employed using real-time COVID-19 data to achieve minimum error.
- The dynamics system was utilized to simulate epidemic trends, followed by an analysis of isolation measures' effectiveness.
Main Results:
- The proposed time-delayed infectious disease model demonstrated improved accuracy in simulating COVID-19 spread.
- Simulations provided insights into the epidemic's development trends in Beijing and Wuhan.
- Comparative analysis highlighted the critical role of early detection and isolation in mitigating epidemic severity.
Conclusions:
- The time-delayed infectious disease model offers a more accurate representation of COVID-19 transmission dynamics.
- Early detection and isolation remain paramount strategies for effective epidemic prevention and control.
- The study underscores the importance of data-driven modeling for public health decision-making during pandemics.
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