Prescriptive Analytics-Based SIRM Model for Predicting Covid-19 Outbreak

Jamal Al Qundus (), Shivam Gupta (), Hesham Abusaimeh (), Silvio Peikert () and Adrian Paschke ()
Additional contact information
Jamal Al Qundus: Middle East University
Shivam Gupta: NEOMA Business School
Hesham Abusaimeh: Middle East University
Silvio Peikert: Fraunhofer, FOKUS
Adrian Paschke: Fraunhofer, FOKUS

Global Journal of Flexible Systems Management, 2023, vol. 24, issue 2, No 5, 235-246

Abstract: Abstract Predicting the outbreak of a pandemic is an important measure in order to help saving people lives threatened by Covid-19. Having information about the possible spread of the pandemic, authorities and people can make better decisions. For example, such analyses help developing better strategies for distributing vaccines and medicines. This paper has modified the original Susceptible-Infectious-Recovered (SIR) model to Susceptible-Immune-Infected-Recovered (SIRM) which includes the Immunity ratio as a parameter to enhance the prediction of the pandemic. SIR is a widely used model to predict the spread of a pandemic. Many types of pandemics imply many variants of the SIR models which make it very difficult to find out the best model that matches the running pandemic. The simulation of this paper used the published data about the spread of the pandemic in order to examine our new SIRM. The results showed clearly that our new SIRM covering the aspects of vaccine and medicine is an appropriate model to predict the behavior of the pandemic.

Keywords: Covid-19; Impact of vaccine and medicine; Mathematical theory of SIR model; Pandemic outbreak prediction; SIR Model (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s40171-023-00337-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:gjofsm:v:24:y:2023:i:2:d:10.1007_s40171-023-00337-0

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/40171

DOI: 10.1007/s40171-023-00337-0

Access Statistics for this article

Global Journal of Flexible Systems Management is currently edited by Sushil

More articles in Global Journal of Flexible Systems Management from Springer, Global Institute of Flexible Systems Management
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().