SEIRV epidemiological model for COVID 19 with Holling type II functional response.

Area of Science:

• Epidemiology
• Mathematical Biology
• Public Health

Background:

• Mathematical models are crucial for understanding infectious disease dynamics.
• Previous models have aided public health research.
• SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) necessitates advanced modeling approaches.

Purpose of the Study:

• To develop and analyze an SEIRV (Susceptible-Exposed-Infectious-Recovered-Vaccinated) mathematical model for SARS-CoV-2.
• To incorporate a Holling type-II functional response for a more realistic representation of disease transmission dynamics.
• To provide a comprehensive analysis using analytical, computational, and statistical tools.

Main Methods:

• Development of a compartmental SEIRV model.
• Integration of a Holling type-II functional response to model disease transmission.
• Derivation of a closed-form expression for the basic reproduction number (R0).
• Sensitivity analysis of model parameters.
• Application of analytical, computational, and statistical methods.

Main Results:

• A novel SEIRV model incorporating a Holling type-II response was developed for SARS-CoV-2.
• A closed-form mathematical expression for the basic reproduction number was derived.
• Predictive intervals for the basic reproduction number were calculated.
• Parameter sensitivity analysis was performed to identify key drivers of disease spread.

Conclusions:

• The developed model offers a robust framework for understanding SARS-CoV-2 transmission dynamics.
• The Holling type-II functional response provides ecological insights into disease spread.
• The analytical and computational results enhance our understanding of infectious disease modeling for public health applications.