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The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 12 No. 3 (2022)

DOI
10.11591/ijece.v12i3.pp2900-2910
ISSN
2722-2578, 2088-8708
Published
2022-06-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The COVID-19 epidemic has spread massively to almost all countries including Indonesia, in just a few months. An important step to overcoming the spread of the COVID-19 is understanding its epidemiology through mathematical modeling intervention. Knowledge of epidemic dynamics patterns is an important part of making timely decisions and preparing hospitals for the outbreak peak. In this study, we developed the susceptible-infected-recovered-dead (SIRD) model, which incorporates the key epidemiological parameters to model and estimate the long-term spread of the COVID-19. The proposed model formulation is data-based analysis using public COVID-19 data from March 2, 2020 to May 15, 2021. Based on numerical analysis, the spread of the pandemic will begin to fade out after November 5, 2021. As a consequence of this virus attack, the cumulative number of infected, recovered, and dead people were estimated at ≈ 3,200,000, ≈ 3,437,000 and ≈ 63,000 people, respectively. Besides, the key epidemiological parameter indicates that the average reproduction number value of COVID-19 in Indonesia is 7.32. The long-term prediction of COVID-19 in Indonesia and its epidemiology can be well described using the SIRD model. The model can be applied in specific regions or cities in understanding the epidemic pattern of COVID-19.

Collaboration network of the authors

18 authors · 73 co-authorship links · 45 across different organisations

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  • IPB University
  • Universitas Airlangga
  • Institut Teknologi Telkom Surabaya
  • Padjadjaran University
  • Politeknik Surabaya
  • Institut Teknologi Sepuluh Nopember
  • Emerge
  • Other organisations
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Christopher AndreasUniversitas Airlangga3
Rika SusantiEmerge3
Hawwin MardhianaInstitut Teknologi Telkom Surabaya3
Ilma Amira RahmayantiUniversitas Airlangga3
Inna NoviantyIPB University2
Walidatush SholihahIPB University2
Gema Parasti MindaraIPB University2
Muhammad Iqbal NurulhaqIPB University2
Rismen SinambelaUniversitas Kristen Indonesia2
Pradeka Brilyan PurwandokoNational Research and Innovation Agency2

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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