A comparative study of modified SIR and logistic predictors using local level database of COVID-19 in India
Information Discovery and Delivery
ISSN: 2398-6247
Article publication date: 10 June 2021
Issue publication date: 22 September 2021
Abstract
Purpose
Several national- and state-level studies have been predicting the course of the COVID-19 pandemic using supervised machine learning algorithms. However, the comparison of such models has not been discussed before. This is the first-ever research wherein the two leading models, susceptible-infected-recovered (SIR) and logistic are compared. The purpose of this study is to observe their utility, at both the National and Municipal Corporation level in India.
Design/methodology/approach
The modified SIR and the logistic were deployed for analysis of the COVID-19 patients’ database of India and three Municipal Corporations, namely, Akola, Kalyan-Dombivli and Mira-Bhayander. The data for the study was collected from the official notifications for COVID-19 released by respective government websites.
Findings
This study provides evidence to show the superiority of the modified SIR over the logistic model. The models give accurate predictions for a period up to 14 days. The prediction accuracy of the models is limited due to change in government policies. This can be observed by the drastic increase in the COVID-19 cases after Unlock 1.0 in India. The models have proven that they can effectively predict for both National and Municipal Corporation level database.
Practical implications
The modified SIR model can be used to signify the practicality and effectiveness of the decisions taken by the authorities to contain the spread of coronavirus.
Originality/value
This study modifies the SIR model and also identifies and fulfills the need to find a more accurate prediction algorithm to help curb the pandemic.
Keywords
Acknowledgements
The authors would like to thank the healthcare professionals, their allied teams and sanitation workers of COVID-19. Additional thanks to Municipal Corporations of Akola, Mira-Bhayander and KDMC and Government of India.
Funding: Not applicable.
Conflicts of interest/Competing interests: There was no conflict of interest.
Citation
Bajaj, N.S., Pardeshi, S.S., Patange, A.D., Khade, H.S. and Mate, K. (2021), "A comparative study of modified SIR and logistic predictors using local level database of COVID-19 in India", Information Discovery and Delivery, Vol. 49 No. 3, pp. 203-215. https://doi.org/10.1108/IDD-09-2020-0112
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited