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Comparison of various epidemic models on the COVID-19 outbreak in Indonesia

Research Center of Informatics, National Research and Innovation Agency. Jl. Sangkuriang, Komplek LIPI Gedung 20 Lt. 3, Bandung 40135, Indonesia

Received: 24 May 2021; Revised: 26 Jul 2021; Accepted: 23 Jan 2021; Published: 31 Jan 2022.
Open Access Copyright (c) 2022 The authors. Published by Department of Computer Engineering, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
This paper compares four mathematical models to describe Indonesia's current coronavirus disease 2019 (COVID-19) pandemic. The daily confirmed case data are used to develop the four models: Logistic, Richards, SIR, and SEIR. A least-square fitting computes each parameter to the available confirmed cases data. We conducted parameterization and sensitivity experiments by varying the length of the data from 60 until 300 days of transmission. All models are susceptible to the epidemic data. Though the correlations between the models and the data are pretty good (>90%), all models still show a poor performance (RMSE>18%). In this study case, Richards model is superior to other models from the highest projection of the positive cases of COVID-19 in Indonesia. At the same time, others underestimate the outbreak and estimate too early decreasing phase. Richards model predicts that the pandemic remains high for a long time, while others project the pandemic will finish much earlier.
Keywords: COVID-19; SEIR; SIR; Richard; Logistic
Funding: National Research and Innovation Agency

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