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Modeling the Waves of Covid-19
1University of North Carolina at Chapel Hill, Chapel Hill, USA. chered@email.unc.edu.
Acta Biotheoretica
|December 27, 2021
Summary
This study introduces a two-phase model for Covid-19 spread, utilizing Bessel functions to accurately forecast epidemic waves. The model explains wave uniformity and is applicable to other fields like behavioral psychology.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Physics
Background:
- Modeling Covid-19 spread faces challenges due to time-dependent exponents in power-type growth and saturation from protective measures.
- Existing models struggle to accurately capture the dynamics of epidemic waves.
Purpose of the Study:
- To develop a novel two-phase model for predicting the total number of detected Covid-19 cases.
- To explain the observed uniformity of Covid-19 waves across different regions.
- To provide a framework for forecasting epidemic spread.
Main Methods:
- A two-phase mathematical solution incorporating Bessel functions is proposed.
- Universal differential equations are derived, applicable to various transient processes.
- Key parameters identified include initial transmission rate and intensity of restriction mechanisms.
Main Results:
- The proposed model accurately describes Covid-19 wave curves in numerous countries, approaching the accuracy of physical laws.
- The model successfully forecasted the third wave in the USA.
- Analysis of Delta-waves in India, South Africa, UK, and the Netherlands is presented.
Conclusions:
- The developed model offers a robust and accurate method for understanding and forecasting epidemic dynamics.
- The underlying differential equations have broad applicability in fields such as behavioral psychology and invasion ecology.
- The model provides a compelling explanation for the consistent patterns observed in Covid-19 waves globally.
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