Epidemic Modeling of COVID-19 in the ASEAN countries using a Genetic Partial Fitting Algorithm with the Presence of a Second Wave

Venansius R.  Tjahjono; Hengky  Kurniawan; Amirul  Hakam; Endah R.M. Putri; Hadi Susanto

doi:10.6180/jase.202112_24(6).0011

Epidemic Modeling of COVID-19 in the ASEAN countries using a Genetic Partial Fitting Algorithm with the Presence of a Second Wave

Venansius R. Tjahjono¹, Hengky Kurniawan¹, Amirul Hakam1, Endah R.M. PutriThis email address is being protected from spambots. You need JavaScript enabled to view it.¹, and
Hadi Susanto^2,3

¹Department of Mathematics, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember, Indonesia
²Department of Mathematics, Khalifa University, United Arab Emirates
³Department of Mathematical Sciences, University of Essex, United Kingdom

Received: February 22, 2021
Accepted: April 27, 2021
Publication Date: June 23, 2021

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202112_24(6).0011

ABSTRACT

We present an SIRD epidemic modelling for COVID-19 outbreak in the ASEAN member countries. The occurrence of a second wave in the region adds complexity to the parameter estimation of the SIRD model. In this case, a standard genetic algorithm cannot fully capture the dynamic transmission of the pandemic. We therefore introduce a genetic partial fitting algorithm (GPFA) of seven-day intervals. We show that our method outperforms the standard algorithm with a significant reduction in the Root Mean Square Error (RMSE) value. We also extend our study to produce a real-time estimation of the effective reproduction number with a confidence interval to incorporate uncertainties in the model.

Keywords: Genetic algorithm, Epidemic model, Partial fitting, Second wave

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