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Generalized Richards model for predicting COVID-19 dynamics in Saudi Arabia based on particle swarm optimization

Rafat Zreiq1,2, Souad Kamel3, Sahbi Boubaker3

  • 1Department of Public Health, College of Public Health and Health Informatics, University of Ha'il, Ha'il, Saudi Arabia.

AIMS Public Health
|December 9, 2020
PubMed
Summary

This study used the Generalized Richards Model (GRM) to predict COVID-19 cases in Saudi Arabia, forecasting an outbreak end by December 2020. The GRM provided the most accurate predictions for case numbers and outbreak duration.

Keywords:
COVID-19 dynamicsGeneralized Richards Model (GRM)Particle Swarm Optimization (PSO)predictionprojected end date

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health

Background:

  • The COVID-19 pandemic poses significant global health, economic, and social challenges.
  • Accurate prediction of virus dynamics is crucial for effective decision-making and mitigation strategies.

Purpose of the Study:

  • To investigate and compare phenomenological epidemic models, including the Suspected-Infected-Recovered (SIR) model, for predicting COVID-19 cumulative cases and outbreak end dates in Saudi Arabia.
  • To identify the most accurate model for forecasting the pandemic's trajectory in the region.

Main Methods:

  • Formulated the prediction problem as an optimization framework.
  • Employed a Particle Swarm Optimization (PSO) algorithm to solve the optimization problem.
  • Evaluated four phenomenological models and the SIR model using data from March 2nd to October 10th, 2020.

Main Results:

  • The Generalized Richards Model (GRM) demonstrated superior performance in fitting the collected data.
  • GRM achieved the lowest Mean Absolute Percentage Error (MAPE) of 3.2889%, highest R-squared (0.9953), and lowest Root Mean Squared Error (RMSE) of 8827.
  • GRM predicted a probable outbreak end date around late December 2020, with an estimated 378,299 total cases.

Conclusions:

  • The Generalized Richards Model (GRM) is highly effective for predicting COVID-19 dynamics in Saudi Arabia.
  • The findings offer valuable insights for public health decision-makers regarding pandemic mitigation and containment.
  • Accurate epidemiological modeling is essential for understanding and managing infectious disease outbreaks.