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Global Journal of Flexible Systems Management
Published in: Global Journal of Flexible Systems Management 2/2023

17-03-2023 | ORIGINAL RESEARCH

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

Authors: Jamal Al Qundus, Shivam Gupta, Hesham Abusaimeh, Silvio Peikert, Adrian Paschke

Published in: Global Journal of Flexible Systems Management | Issue 2/2023

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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.
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Footnotes
4
After the experience we have had in dealing with information coming from the authoritarian.
 
5
In terms of the spread degree at time t.
 
6
b should be, therefore, maximized. Such factors can be immune system or measures against an infection.
 
7
Thus, no longer susceptible to the disease.
 
8
Thus, no longer belong to the infected group.
 
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Metadata
Title
Prescriptive Analytics-Based SIRM Model for Predicting Covid-19 Outbreak
Authors
Jamal Al Qundus
Shivam Gupta
Hesham Abusaimeh
Silvio Peikert
Adrian Paschke
Publication date
17-03-2023
Publisher
Springer India
Published in
Global Journal of Flexible Systems Management / Issue 2/2023
Print ISSN: 0972-2696
Electronic ISSN: 0974-0198
DOI
https://doi.org/10.1007/s40171-023-00337-0

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