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Optimal time-dependent SUC model for COVID-19 pandemic in India
Youngjin Hwang1, Soobin Kwak1, Jyoti2
1Department of Mathematics, Korea University, Seoul, 02841, State, Republic of Korea.
BMC Infectious Diseases
|September 28, 2024
Summary
This study introduces a numerical algorithm to estimate optimal epidemic parameters for the time-dependent Susceptible-Unidentified infected-Confirmed (tSUC) model. The method adaptively calculates time-dependent transmission rates for infectious disease modeling, crucial for analyzing pandemics like COVID-19 in India.
Area of Science:
- Epidemiology
- Computational Biology
- Mathematical Modeling
Background:
- The Susceptible-Unidentified infected-Confirmed (tSUC) model is essential for understanding infectious disease dynamics, especially unconfirmed cases.
- Epidemic parameters, particularly transmission rates, can vary significantly due to interventions and disease progression.
- Accurate estimation of time-dependent transmission rates is vital for effective pandemic response.
Purpose of the Study:
- To propose a novel numerical algorithm for determining optimal epidemic parameters within a time-dependent tSUC model.
- To adaptively estimate time-dependent transmission rates using real-world data, specifically cumulative confirmed cases.
- To validate the algorithm's performance in accurately modeling infectious disease spread.
Main Methods:
- Development of a numerical algorithm to estimate optimal parameters for the tSUC model.
- Adaptive estimation of time-dependent transmission rates based on identified linear change points in confirmed case data.
- Preprocessing and smoothing of cumulative confirmed case data from India to identify key change points.
- Interpolation of transmission rates between change points and minimization of discrepancies using a least-squares approach.
Main Results:
- The proposed algorithm successfully calculates optimal time-dependent parameters for the tSUC model.
- Numerical experiments validated the algorithm's ability to accurately represent the dynamics of confirmed cases.
- The algorithm provides a reliable time-dependent transmission rate for the COVID-19 pandemic in India.
Conclusions:
- The developed numerical algorithm effectively estimates optimal time-dependent epidemic parameters for the tSUC model.
- This approach offers a robust method for analyzing infectious disease transmission, particularly for time-varying rates.
- The calculated time-dependent transmission rates can inform public health strategies and pandemic analysis, exemplified by the COVID-19 data from India.
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