ACADSTAFF UGM

CREATION
Title : Real-time Forecasting of the COVID-19 Epidemic using the Richards Model in South Sulawesi
Author :

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

Date : 1 2020
Keyword : COVID-19; real-time forecast; Richards model; South Sulawesi; Indonesia COVID-19; real-time forecast; Richards model; South Sulawesi; Indonesia
Abstract : This paper discussed Real-time Forecasting of the COVID-19 Epidemic using daily cumulative cases of COVID-19 in South Sulawesi. Our aim is to make model for the growth of COVID-19 cases in South Sulawesi in the top 5 provinces with the largest COVID-19 cases in Indonesia and predict when this pandemic reaches the peak of spread and when it ends. This paper used the Richards model, which is an extension of a simple logistic growth model with additional scaling parameters. Data used in the paper as of June 24, 2020 were taken from the official website of the Indonesian government. Our results are that the maximum cumulative number of COVID-19 cases has reached 10,000 to 12,000 cases. The peak of the pandemic is estimated to occur from June to July 2020 while continuing to impose social restrictions. The condition in South Sulawesi shows a sloping curve around October 2020, which means that there are still additional cases but not significant. When entering November, the curve starts to flat which indicates the addition of very small cases until the pandemic ends. The results of the pandemic peak prediction are the same as the Indonesian data; what is different is the prediction of when the pandemic will end. In the best-case scenario, the current data will tend to slow down, with the COVID-19 pandemic in South Sulawesi expected to end in November 2020. Our modeling procedure can provide information about the ongoing COVID-19 pandemic in South Sulawesi that may facilitate real-time public health responses about future disease outbreaks
Group of Knowledge : Statistik
Original Language : English
Level : Internasional
Status :
Published
Document
No Title Document Type Action
1 2020 Ike UPI paper.pdf
Document Type : [PAK] Full Dokumen
[PAK] Full Dokumen View
2 2020 Ike UPI paper.pdf
Document Type : [PAK] Cek Similarity
[PAK] Cek Similarity View