ACADSTAFF UGM

CREATION
Title : Data-driven Analysis and Prediction of COVID-19 Infection in Southeast Asia using A Phenomenological Model
Author :

FAIHATUZ ZUHAIROH (1) Prof. Dr.rer.nat. Dedi Rosadi, S.Si., M.Sc. (2)

Date : 1 2022
Keyword : COVID-19,data-driven,prediction,Richards curve,logistic growth model, Southeast Asia COVID-19,data-driven,prediction,Richards curve,logistic growth model, Southeast Asia
Abstract : COVID-19 has spread throughout the world, including in Southeast Asia. Many studies have made predictions using various models. However, very few are data-driven based. Meanwhile for the COVID-19 case, which is still ongoing, it is very suitable to use data-driven approach with phenomenological models. This paper aimed to obtain effective forecasting models and then predict when COVID-19 in Southeast Asia will peak and end using daily cumulative case data. The research applied the Richards curve and the logistic growth model, combining the two models to make prediction of the COVID-19 cases in Southeast Asia, both the countries with one pandemic wave or those with more than one pandemic wave. The best prediction results were obtained using the Richards curve with the logistic growth model parameters used as the initial values. In the best scenario, the Southeast Asia region is expected to be free from the COVID-19 pandemic at the end of 2021. These modeling results are expected to provide information about the provision of health facilities and how to handle infectious disease outbreaks in the future.
Group of Knowledge : Statistik
Original Language : English
Level : Internasional
Status :
Published
Document
No Title Document Type Action
1 3714-Full Text Article-15925-2-10-20220306.pdf
Document Type : [PAK] Full Dokumen
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2 L1 Ike DR PJSOR 2022.pdf
Document Type : Dokumen Pendukung Karya Ilmiah (Hibah, Publikasi, Penelitian, Pengabdian)
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3 2022 DR Ike pjsor.pdf
Document Type : [PAK] Bukti Korespondensi Penulis
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