Predicting optimal lockdown period with parametric approach using three-phase maturation SIRD model for COVID-19...

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• COVID-19 transmission poses significant public health and economic challenges.
• Existing models often lack parameters crucial for accurate prediction and economic impact assessment.

Purpose of the Study:

• To propose a novel three-phase Susceptible-Infected-Recovered-Dead (3P-SIRD) model for calculating optimal COVID-19 lockdown periods.
• To incorporate factors like silent carriers, sociability, unregistered deaths, and variable testing rates for enhanced accuracy.
• To balance epidemic control with economic recovery and infrastructure support.

Main Methods:

• Development of a three-phase SIRD model (3P-SIRD) incorporating novel parameters.
• Inclusion of silent carriers, sociability of infected individuals, unregistered deaths, and phase-dependent testing rates.
• Validation of the model using data from China to predict optimal lockdown duration.

Main Results:

• The 3P-SIRD model accurately reflects COVID-19 case data in China.
• The model predicted an optimal lockdown period of 73 days for China, closely matching the actual 77 days.
• The model's efficacy was demonstrated for predicting optimal lockdown periods in India and Italy.

Conclusions:

• The proposed 3P-SIRD model offers a more comprehensive approach to epidemic modeling.
• It provides a valuable tool for determining optimal lockdown strategies that consider both public health and economic factors.
• The model's predictive accuracy supports its application for future pandemic preparedness and response planning.