EMPIRICAL MODELING FOR REPORTED CASES AND DEATHS OF COVID-19 IN EGYPT DURING THE ACCELERATED SPREAD AND PREDICTION OF THE DELAYED PHASE

Kotb, Essam; Ouerfelli, Noureddine; Zrelli, Naouel; Briki, Khaoula; Ahmed, Asmaa A.; Medhat, Mohammed A.; Elsayed, Hassan; El-Kassas, Mohamed

doi:10.21608/bfsa.2022.271639

EMPIRICAL MODELING FOR REPORTED CASES AND DEATHS OF COVID-19 IN EGYPT DURING THE ACCELERATED SPREAD AND PREDICTION OF THE DELAYED PHASE

Document Type : Original Article

Authors

¹ Department of Biology, College of Science, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia- Basic & Applied Scientific Research Center, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.

² Department of Chemistry, College of Science, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.

³ LAMSIN, Laboratoire de Modélisation Mathématique et Numérique dans les Sciences de l'Ingénieur, Ecole Nationale d’Ingénieurs de Tunis, B.P. 37, 1002 Tunis, Tunisie.

⁴ Basic & Applied Scientific Research Center, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia- Department of Mathematics, College of Science, Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam 31441, Saudi Arabia.

⁵ Department of Statistics, Faculty of Commerce, Al-Azhar University (Girls’ Branch), Nasr City, P.N.Box: 11884, Cairo, Egypt.

⁶ Tropical Medicine and Gastroenterology Department, Assiut University, Assiut, Egypt.

⁷ Microbial Biotechnology Department, Biotechnology Research Institute, National Research Centre, Dokki, Cairo, Egypt.

⁸ Endemic Medicine Department, Faculty of Medicine, Helwan University, Cairo, Egypt

10.21608/bfsa.2022.271639

Abstract

This is a newly developed conceivable mathematical model for analyzing the spreading behavior of COVID-19 during the first wave of the pandemic in Egypt. We emphasized the impact of detection and control measures in flattening the spread of disease. This knowledge of the early spread dynamics of infection and assessing the efficiency of control measures is critical for reviewing and evaluating the potential for sustained transmission to occur during the coming waves. This proposed empirical model for the accelerated spread phase is based on non-linear regression technique, interpolations, tangents, least-square, and optimization methods to delimit different phases of the pandemic and predict the delayed phase. We prove that our model is mathematically consistent and present various simulation results using the best-estimated parameter value. The model can be easily updated when restrictions and other issues become changed. These simulation results may guide the local authorities to make timely right decisions.

Keywords