Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023)

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Comprehensive Review on Statistical Modeling Approach to Predict the COVID-19 Transmission

Authors
Vallaippan Raman1, *, Navin Aravinth1, Preetha Merlin Joy1, Kowsalya1
1Department of Artificial Intelligence and Data Science, Coimbatore Institute of Technology, Coimbatore, India
*Corresponding author. Email: valliappan@cit.edu.in
Corresponding Author
Vallaippan Raman
Available Online 10 May 2023.
DOI
10.2991/978-94-6463-162-3_11How to use a DOI?
Keywords
Forecasting; COVID-19; Statistical Models; Machine Learning Methods
Abstract

This study aims to focus on the statistical model for forecasting the transmission of covid-19. The dynamics of the spreading nature can be determined by prediction models. Various prediction models are devised and/or used to know the disease dynamics and the existing ones based on statistical models are being developed for single or multiple countries. Many review articles commonly address the statistical models adopted, whereas the studies indicate effective models that address disease dynamics and forecast potential contagion scenarios viz. Data-driven techniques were created on different parameters. This work aims at collating the basic working philosophies of most cited COVID-19 dynamic prediction model reports by a systematic literature study. The review highlights the dynamic models strength and their weakness in predicting of SARS Covid-19. words.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
10 May 2023
ISBN
10.2991/978-94-6463-162-3_11
ISSN
2352-5428
DOI
10.2991/978-94-6463-162-3_11How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Vallaippan Raman
AU  - Navin Aravinth
AU  - Preetha Merlin Joy
AU  - Kowsalya
PY  - 2023
DA  - 2023/05/10
TI  - Comprehensive Review on Statistical Modeling Approach to Predict the COVID-19 Transmission
BT  - Proceedings of the International Conference on Emerging Trends in Business & Management (ICETBM 2023)
PB  - Atlantis Press
SP  - 112
EP  - 129
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-162-3_11
DO  - 10.2991/978-94-6463-162-3_11
ID  - Raman2023
ER  -