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286227

Nonlinear Statistical models for COVID-19 fourth wave cases in Egypt

Article

Last updated: 25 Dec 2024

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Abstract

Abstract
This study aimed to apply the nonlinear models (Gompertz, Richards', and Weibull) that enables us to study and forecast the daily number of COVID-19 cases in Egypt and determine which of them is the suitable to describe the data of COVID-19 fourth wave cases during the period from 28th of July, 2021 to 5 th January, 2022.The models' parameters were estimated, and the Comparison of these models' fits was made using some statistics (F-test,R^2, AIC, BIC, AICc, and MAPE). Applied on “nonlinear regression" tool available in SPSS-26, and Microsoft excel 2016. According to the highest F and R^2, and lowest values for RMSE, Bias, MAE, AIC, BIC, and AICc, the results indicate that the Weibull model is the best adequate model for studying the daily number of COVID-19 cases in Egypt. The proposed Weibull model is statistically significant for describing the study data.
In this study, the growth curve of real data sets (the daily number of fourth wave COVID-19 cases in Egypt) was examined using three sigmoidal growth models (Gompertz, Richards, and Weibull).

DOI

10.21608/csj.2023.286227

Keywords

Weibull model, Gompertz model, Richards’ model

Authors

First Name

مها

Last Name

توفيق

MiddleName

-

Affiliation

کلية التجارة جامعة طنطا

Email

maha.ibrahim@commerce.tanta.edu.eg

City

ينها

Orcid

-

Volume

9

Article Issue

15

Related Issue

39663

Issue Date

2023-01-01

Receive Date

2022-06-19

Publish Date

2023-01-01

Page Start

330

Page End

346

Print ISSN

2356-9255

Online ISSN

2356-9263

Link

https://csj.journals.ekb.eg/article_286227.html

Detail API

https://csj.journals.ekb.eg/service?article_code=286227

Order

286,227

Type

المقالة الأصلية

Type Code

1,297

Publication Type

Journal

Publication Title

مجلة الدراسات التجارية المعاصرة

Publication Link

https://csj.journals.ekb.eg/

MainTitle

Nonlinear Statistical models for COVID-19 fourth wave cases in Egypt

Details

Type

Article

Created At

25 Dec 2024