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Numerical Simulation to Predict COVID-19 Cases in Punjab.

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Area of Science:

  • Epidemiology
  • Computational Mathematics

Background:

  • Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused Coronavirus disease 2019 (COVID-19), first detected in India on January 30, 2020.
  • Understanding disease transmission dynamics is crucial for effective public health interventions.

Purpose of the Study:

  • To calculate COVID-19 cases in Punjab using advanced numerical methods.
  • To analyze cross-border transmission patterns influenced by human activity.

Main Methods:

  • Solving partial differential equations with modified cubic B-spline functions.
  • Employing the differential quadrature method for numerical simulation.
  • Utilizing real COVID-19 case data and Google Community Mobility Reports for validation.

Main Results:

  • Numerical simulations were verified against actual COVID-19 case data.
  • Google mobility data provided insights into real-time social behavior changes impacting transmission.
  • The model demonstrated predictive capabilities for COVID-19 spread across Punjab's districts.

Conclusions:

  • The developed model accurately simulates COVID-19 transmission in Punjab.
  • Human mobility patterns are significant factors in disease spread and require consideration in control strategies.
  • The study highlights the utility of computational modeling in public health surveillance.