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COVID-19 pandemic in India: a mathematical model study
Sudhanshu Kumar Biswas1, Jayanta Kumar Ghosh2, Susmita Sarkar2
1Sripat Singh College, Murshidabad, West Bengal India.
Nonlinear Dynamics
|September 28, 2020
Summary
Mathematical modeling of COVID-19 in India reveals key transmission parameters and effective preventive strategies. This study provides predictions for future trends under various control measures to manage the pandemic.
Area of Science:
- Epidemiology
- Mathematical Biology
- Public Health
Background:
- The novel coronavirus (SARS-CoV-2) outbreak presents a global health emergency with no immediate vaccine or antiviral treatment.
- India's high population density poses unique challenges for controlling the rapid human-to-human transmission of COVID-19.
Purpose of the Study:
- To develop and parameterize a deterministic compartmental model for studying COVID-19 spread in India.
- To identify influential parameters affecting disease dynamics and evaluate preventive strategies.
- To predict future transmission trends under different control scenarios.
Main Methods:
- Formulation of a deterministic compartmental mathematical model.
- Parameter estimation by fitting the model to reported COVID-19 data from India.
- Sensitivity analysis to determine influential model parameters.
- Estimation of the basic and effective reproduction numbers.
Main Results:
- Identified key parameters influencing COVID-19 transmission dynamics in India.
- Estimated the basic reproduction number (R0) and studied the effective reproduction number (Rt).
- Evaluated the impact of various preventive measures on disease spread.
- Provided predictions for future virus transmission under implemented control strategies.
Conclusions:
- Mathematical modeling is crucial for understanding disease dynamics and informing prevention strategies for pandemics like COVID-19.
- Sensitivity analysis helps pinpoint critical factors for effective control.
- The study underscores the importance of data-driven predictions for managing public health crises.
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