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How complex is COVID-19: Spatiotemporal variation of chaotic nature of the virus in Indian states.

Indian journal of public health·2023

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COVID-19 disease spread modeling by QSIR method: The parameter optimal control approach.

Peri Subrahmanya Hari Prasad¹

¹CORAL, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India.

Clinical Epidemiology and Global Health

|December 20, 2021

Summary

This study modified the SIR model to predict COVID-19 cases in India, finding that lockdowns significantly reduce projected infections. The enhanced model offers crucial insights for public health strategies.

Keywords:

Next generation matrix Parameter optimal control QSIR model Reproduction number SARS-COV-2

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Area of Science:

Epidemiology
Mathematical Modeling
Public Health

Background:

India experienced a significant second wave of SARS-CoV-2, ranking second globally in confirmed cases and third in COVID-19 deaths.
Accurate long-term projections are essential for mitigating the impact of the pandemic in India.

Purpose of the Study:

To modify the conventional SIR model by incorporating a quarantine compartment (Q) to analyze the impact of COVID-19.
To utilize parameter optimal control techniques for curve fitting and estimation of infection and susceptible individuals.

Main Methods:

Modified SIR (Susceptible-Infectious-Recovered) model with an added quarantine (Q) compartment.
Parameter optimal control technique for curve fitting and estimation of epidemiological parameters.

Main Results:

The model predicted a cumulative case count of 2.6928E7 with 99.3% accuracy by May 25, 2020.
Future projections indicated significantly lower case numbers with lockdown measures (3.48E7) compared to periodic lockdowns (3.80E7) or no lockdown (4.52E7).
The estimated basic reproduction number (R0) was 1.1475, with model accuracy at 99% and projection accuracy around 94% up to November 1, 2021.

Conclusions:

The modified SIR model initially overestimated cases but showed a decreasing trend over time.
Model accuracy diminishes with increased time duration, suggesting the need for more control points in the cost function for improved long-term fitting.