The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases

Amir Ahmad; Santosh Kumar Ray; Ch Aswani Kumar; Apurva Anand; Muhsin Jabbar Cheratta

doi:10.1109/I-SMAC52330.2021.9641006

The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases

Amir Ahmad
, Santosh Kumar Ray
, Ch Aswani Kumar
, Apurva Anand
, Muhsin Jabbar Cheratta

Department of Information System and Security

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Coronavirus disease (Covid-19) is a serious health problem for the world. Most of the countries are affected by this infectious disease. Many countries have started vaccination against Covid-19. The number of confirmed cases every day changes rapidly. Public health planners want to know these numbers in advance to arrange health facilities accordingly. Many machine learning models have been developed for the prediction of the number of Covid-infected people. The accuracy of these models depends upon the training data. Data collected during the period when there is no vaccination and data collected during the vaccination period have different properties. The models trained on different datasets perform differently. In this paper, we study the effect of the data collected during the vaccination period. The study will be helpful in generating more accurate prediction models for the vaccination period.

Original language	English
Title of host publication	Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	286-289
Number of pages	4
ISBN (Electronic)	9781665426428
DOIs	https://doi.org/10.1109/I-SMAC52330.2021.9641006
Publication status	Published - 2021
Event	5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021 - Palladam, India Duration: Nov 11 2021 → Nov 13 2021

Publication series

Name	Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021

Conference

Conference	5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021
Country/Territory	India
City	Palladam
Period	11/11/21 → 11/13/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Covid-19
confirmed cases
regression methods
vaccination

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Information Systems
Information Systems and Management
Health Informatics
Communication

Access to Document

10.1109/I-SMAC52330.2021.9641006

Cite this

Ahmad, A., Ray, S. K., Kumar, C. A., Anand, A., & Cheratta, M. J. (2021). The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases. In Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021 (pp. 286-289). (Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/I-SMAC52330.2021.9641006

The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases. / Ahmad, Amir; Ray, Santosh Kumar; Kumar, Ch Aswani et al.
Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 286-289 (Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ahmad, A, Ray, SK, Kumar, CA, Anand, A & Cheratta, MJ 2021, The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases. in Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021. Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 286-289, 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021, Palladam, India, 11/11/21. https://doi.org/10.1109/I-SMAC52330.2021.9641006

Ahmad A, Ray SK, Kumar CA, Anand A, Cheratta MJ. The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases. In Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 286-289. (Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021). doi: 10.1109/I-SMAC52330.2021.9641006

Ahmad, Amir ; Ray, Santosh Kumar ; Kumar, Ch Aswani et al. / The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases. Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 286-289 (Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021).

@inproceedings{657c9e36f2d84b05bb08703d6f6fc3a7,

title = "The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases",

abstract = "Coronavirus disease (Covid-19) is a serious health problem for the world. Most of the countries are affected by this infectious disease. Many countries have started vaccination against Covid-19. The number of confirmed cases every day changes rapidly. Public health planners want to know these numbers in advance to arrange health facilities accordingly. Many machine learning models have been developed for the prediction of the number of Covid-infected people. The accuracy of these models depends upon the training data. Data collected during the period when there is no vaccination and data collected during the vaccination period have different properties. The models trained on different datasets perform differently. In this paper, we study the effect of the data collected during the vaccination period. The study will be helpful in generating more accurate prediction models for the vaccination period.",

keywords = "Covid-19, confirmed cases, regression methods, vaccination",

author = "Amir Ahmad and Ray, \{Santosh Kumar\} and Kumar, \{Ch Aswani\} and Apurva Anand and Cheratta, \{Muhsin Jabbar\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021 ; Conference date: 11-11-2021 Through 13-11-2021",

year = "2021",

doi = "10.1109/I-SMAC52330.2021.9641006",

language = "English",

series = "Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "286--289",

booktitle = "Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021",

}

TY - GEN

T1 - The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases

AU - Ahmad, Amir

AU - Ray, Santosh Kumar

AU - Kumar, Ch Aswani

AU - Anand, Apurva

AU - Cheratta, Muhsin Jabbar

PY - 2021

Y1 - 2021

N2 - Coronavirus disease (Covid-19) is a serious health problem for the world. Most of the countries are affected by this infectious disease. Many countries have started vaccination against Covid-19. The number of confirmed cases every day changes rapidly. Public health planners want to know these numbers in advance to arrange health facilities accordingly. Many machine learning models have been developed for the prediction of the number of Covid-infected people. The accuracy of these models depends upon the training data. Data collected during the period when there is no vaccination and data collected during the vaccination period have different properties. The models trained on different datasets perform differently. In this paper, we study the effect of the data collected during the vaccination period. The study will be helpful in generating more accurate prediction models for the vaccination period.

AB - Coronavirus disease (Covid-19) is a serious health problem for the world. Most of the countries are affected by this infectious disease. Many countries have started vaccination against Covid-19. The number of confirmed cases every day changes rapidly. Public health planners want to know these numbers in advance to arrange health facilities accordingly. Many machine learning models have been developed for the prediction of the number of Covid-infected people. The accuracy of these models depends upon the training data. Data collected during the period when there is no vaccination and data collected during the vaccination period have different properties. The models trained on different datasets perform differently. In this paper, we study the effect of the data collected during the vaccination period. The study will be helpful in generating more accurate prediction models for the vaccination period.

KW - Covid-19

KW - confirmed cases

KW - regression methods

KW - vaccination

UR - https://www.scopus.com/pages/publications/85124222951

UR - https://www.scopus.com/pages/publications/85124222951#tab=citedBy

U2 - 10.1109/I-SMAC52330.2021.9641006

DO - 10.1109/I-SMAC52330.2021.9641006

M3 - Conference contribution

AN - SCOPUS:85124222951

T3 - Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021

SP - 286

EP - 289

BT - Proceedings of the 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2021

Y2 - 11 November 2021 through 13 November 2021

ER -

The study of the effect of the data collected during vaccination period on the prediction of the number of Covid-19 cases

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this