Parameter Estimation and Early Dynamics of COVID-19 Disease

H. Sharma; M. Mathur; S. D. Purohit; K. M. Owolabi; K. S. Nisar

doi:10.1007/978-981-16-5348-3_62

Parameter Estimation and Early Dynamics of COVID-19 Disease

H. Sharma
, M. Mathur
, S. D. Purohit
, K. M. Owolabi
, K. S. Nisar

Mathematics

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

4 Scopus citations

Abstract

In this article, we have considered nine countries where the epidemic shows steady state or has a rising trend and used the traditional SEIR model to estimate the parameter for COVID-19 disease. These parameters are contact rate, removal rate, basic reproduction number, initial doubling time, point of inflection, and epidemic rate. In another part of the work, we have considered five countries where the epidemic trend has not settled and used exponential smoothing technique to forecast the infected cases. The study reports a magnifiable concern for reducing the transmission rate in order to combat the disease.

Original language	English
Title of host publication	Proceedings of International Conference on Data Science and Applications, ICDSA 2021
Editors	Mukesh Saraswat, Sarbani Roy, Chandreyee Chowdhury, Amir H. Gandomi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	783-795
Number of pages	13
ISBN (Print)	9789811653476
DOIs	https://doi.org/10.1007/978-981-16-5348-3_62
State	Published - 2022
Event	2nd International Conference on Data Science and Applications, ICDSA 2021 - Virtual, Online Duration: 10 Apr 2021 → 11 Apr 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	287
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	2nd International Conference on Data Science and Applications, ICDSA 2021
City	Virtual, Online
Period	10/04/21 → 11/04/21

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Computational methods
COVID-19
Epidemiology
SARS CoV-2
SEIR model

Access to Document

10.1007/978-981-16-5348-3_62

Cite this

Sharma, H., Mathur, M., Purohit, S. D., Owolabi, K. M., & Nisar, K. S. (2022). Parameter Estimation and Early Dynamics of COVID-19 Disease. In M. Saraswat, S. Roy, C. Chowdhury, & A. H. Gandomi (Eds.), Proceedings of International Conference on Data Science and Applications, ICDSA 2021 (pp. 783-795). (Lecture Notes in Networks and Systems; Vol. 287). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-5348-3_62

Sharma, H. ; Mathur, M. ; Purohit, S. D. et al. / Parameter Estimation and Early Dynamics of COVID-19 Disease. Proceedings of International Conference on Data Science and Applications, ICDSA 2021. editor / Mukesh Saraswat ; Sarbani Roy ; Chandreyee Chowdhury ; Amir H. Gandomi. Springer Science and Business Media Deutschland GmbH, 2022. pp. 783-795 (Lecture Notes in Networks and Systems).

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title = "Parameter Estimation and Early Dynamics of COVID-19 Disease",

abstract = "In this article, we have considered nine countries where the epidemic shows steady state or has a rising trend and used the traditional SEIR model to estimate the parameter for COVID-19 disease. These parameters are contact rate, removal rate, basic reproduction number, initial doubling time, point of inflection, and epidemic rate. In another part of the work, we have considered five countries where the epidemic trend has not settled and used exponential smoothing technique to forecast the infected cases. The study reports a magnifiable concern for reducing the transmission rate in order to combat the disease.",

keywords = "Computational methods, COVID-19, Epidemiology, SARS CoV-2, SEIR model",

author = "H. Sharma and M. Mathur and Purohit, \{S. D.\} and Owolabi, \{K. M.\} and Nisar, \{K. S.\}",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 2nd International Conference on Data Science and Applications, ICDSA 2021 ; Conference date: 10-04-2021 Through 11-04-2021",

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Sharma, H, Mathur, M, Purohit, SD, Owolabi, KM & Nisar, KS 2022, Parameter Estimation and Early Dynamics of COVID-19 Disease. in M Saraswat, S Roy, C Chowdhury & AH Gandomi (eds), Proceedings of International Conference on Data Science and Applications, ICDSA 2021. Lecture Notes in Networks and Systems, vol. 287, Springer Science and Business Media Deutschland GmbH, pp. 783-795, 2nd International Conference on Data Science and Applications, ICDSA 2021, Virtual, Online, 10/04/21. https://doi.org/10.1007/978-981-16-5348-3_62

Parameter Estimation and Early Dynamics of COVID-19 Disease. / Sharma, H.; Mathur, M.; Purohit, S. D. et al.
Proceedings of International Conference on Data Science and Applications, ICDSA 2021. ed. / Mukesh Saraswat; Sarbani Roy; Chandreyee Chowdhury; Amir H. Gandomi. Springer Science and Business Media Deutschland GmbH, 2022. p. 783-795 (Lecture Notes in Networks and Systems; Vol. 287).

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

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AB - In this article, we have considered nine countries where the epidemic shows steady state or has a rising trend and used the traditional SEIR model to estimate the parameter for COVID-19 disease. These parameters are contact rate, removal rate, basic reproduction number, initial doubling time, point of inflection, and epidemic rate. In another part of the work, we have considered five countries where the epidemic trend has not settled and used exponential smoothing technique to forecast the infected cases. The study reports a magnifiable concern for reducing the transmission rate in order to combat the disease.

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Sharma H, Mathur M, Purohit SD, Owolabi KM, Nisar KS. Parameter Estimation and Early Dynamics of COVID-19 Disease. In Saraswat M, Roy S, Chowdhury C, Gandomi AH, editors, Proceedings of International Conference on Data Science and Applications, ICDSA 2021. Springer Science and Business Media Deutschland GmbH. 2022. p. 783-795. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-16-5348-3_62