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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)901-914
Number of pages14
JournalJournal of Applied Science and Engineering (Taiwan)
Volume24
Issue number6
DOIs
Publication statusPublished - 2021

Keywords

  • Epidemic model
  • Genetic algorithm
  • Partial fitting
  • Second wave

Fingerprint

Dive into the research topics of 'Epidemic modeling of COVID-19 in the ASEAN countries using a genetic partial fitting algorithm with the presence of a second wave'. Together they form a unique fingerprint.

Cite this