Equation-Based Modeling vs. Agent-Based Modeling with Applications to the Spread of COVID-19 Outbreak

Selain K. Kasereka, Glody N. Zohinga, Vogel M. Kiketa, Ruffin-Benoît M. Ngoie, Eddy K. Mputu, Nathanaël M. Kasoro and Kyamakya Kyandoghere
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Selain K. Kasereka: Mathematics, Statistics and Computer Science Department, University of Kinshasa, Kinshasa, Congo
Glody N. Zohinga: Mathematics, Statistics and Computer Science Department, University of Kinshasa, Kinshasa, Congo
Vogel M. Kiketa: Business English and Computer Science Department, University of Kinshasa, Kinshasa, Congo
Ruffin-Benoît M. Ngoie: Artificial Intelligence, Big Data and Modeling Simulation Research Center (ABIL), Kinshasa, Congo
Eddy K. Mputu: Artificial Intelligence, Big Data and Modeling Simulation Research Center (ABIL), Kinshasa, Congo
Nathanaël M. Kasoro: Mathematics, Statistics and Computer Science Department, University of Kinshasa, Kinshasa, Congo
Kyamakya Kyandoghere: Institute of Smart Systems Technologies, University of Klagenfurt, 9020 Klagenfurt, Austria

Mathematics, 2023, vol. 11, issue 1, 1-21

Abstract: In this paper, we explore two modeling approaches to understanding the dynamics of infectious diseases in the population: equation-based modeling (EBM) and agent-based modeling (ABM). To achieve this, a comparative study of these approaches was conducted and we highlighted their advantages and disadvantages. Two case studies on the spread of the COVID-19 pandemic were carried out using both approaches. The results obtained show that differential equation-based models are faster but still simplistic, while agent-based models require more machine capabilities but are more realistic and very close to biology. Based on these outputs, it seems that the coupling of both approaches could be an interesting compromise.

Keywords: COVID-19; basic reproduction number; virus spread; modeling simulation; agent-based modeling; equation-based modeling (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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