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Mathematical modeling for novel coronavirus (COVID-19) and control.
Marei Saeed Alqarni1, Metib Alghamdi1, Taseer Muhammad1
1Department of Mathematics, College of Sciences King Khalid University Abha Saudi Arabia.
Numerical Methods for Partial Differential Equations
|December 28, 2020
Summary
This study models COVID-19 transmission in Saudi Arabia, estimating a basic reproduction number (R0) of approximately 1.29. Identifying sensitive parameters can guide control strategies to reduce infection spread.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Infectious Disease Dynamics
Background:
- The COVID-19 pandemic posed a significant global health challenge.
- Understanding transmission dynamics is crucial for effective control.
Purpose of the Study:
- To develop a mathematical model for COVID-19 transmission in Saudi Arabia.
- To estimate key epidemiological parameters, including the basic reproduction number (R0).
- To identify sensitive parameters for control strategy development.
Main Methods:
- Mathematical modeling of disease transmission.
- Least squares curve fitting for parameter estimation.
- Analysis of model stability based on R0.
- Polynomial Ridge Correlation (PRCC) method for sensitivity analysis.
Main Results:
- A mathematical model for COVID-19 transmission was constructed.
- The basic reproduction number (R0) was estimated at approximately 1.2937.
- Model stability was confirmed for R0 < 1.
- Key sensitive parameters influencing R0 were identified.
Conclusions:
- The model provides insights into COVID-19 transmission dynamics in Saudi Arabia.
- Identified sensitive parameters can inform targeted public health interventions.
- Implementing suggested control measures can significantly reduce infection rates.
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