Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries

doi:10.1016/j.chaos.2020.110086

. 2020 Oct:139:110086.

doi: 10.1016/j.chaos.2020.110086. Epub 2020 Jul 4.

Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries

Sarbjit Singh^{1

2}, Kulwinder Singh Parmar³, Sidhu Jitendra Singh Makkhan^{4

5}, Jatinder Kaur^{3

6}, Shruti Peshoria⁷, Jatinder Kumar²

Affiliations

¹ Guru Nanak Dev University College, Narot Jaimal Singh, Pathankot, Punjab, India.
² Department of Mathematics, Guru Nanak Dev University, Amritsar, Punjab, India.
³ Department of Mathematics, I.K. Gujral Punjab Technical University, Punjab, India.
⁴ Department of Mathematics, Sri Guru Angad Dev College, Khadoor Sahib, Tarn Taran, Punjab, India.
⁵ Department of Mathematics, Lovely Professional University, Punjab, India.
⁶ Guru Nanak Dev University College, Verka, Amritsar, Punjab, India.
⁷ Centre for Fire, Explosive and Environment Safety (CFEES), Defence Research and Development Organisation (DRDO), Timarpur, Delhi 110054, India.

PMID: 32834622
PMCID: PMC7345281
DOI: 10.1016/j.chaos.2020.110086

Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries

Sarbjit Singh et al. Chaos Solitons Fractals. 2020 Oct.

. 2020 Oct:139:110086.

doi: 10.1016/j.chaos.2020.110086. Epub 2020 Jul 4.

Authors

Sarbjit Singh^{1

2}, Kulwinder Singh Parmar³, Sidhu Jitendra Singh Makkhan^{4

5}, Jatinder Kaur^{3

6}, Shruti Peshoria⁷, Jatinder Kumar²

Affiliations

¹ Guru Nanak Dev University College, Narot Jaimal Singh, Pathankot, Punjab, India.
² Department of Mathematics, Guru Nanak Dev University, Amritsar, Punjab, India.
³ Department of Mathematics, I.K. Gujral Punjab Technical University, Punjab, India.
⁴ Department of Mathematics, Sri Guru Angad Dev College, Khadoor Sahib, Tarn Taran, Punjab, India.
⁵ Department of Mathematics, Lovely Professional University, Punjab, India.
⁶ Guru Nanak Dev University College, Verka, Amritsar, Punjab, India.
⁷ Centre for Fire, Explosive and Environment Safety (CFEES), Defence Research and Development Organisation (DRDO), Timarpur, Delhi 110054, India.

PMID: 32834622
PMCID: PMC7345281
DOI: 10.1016/j.chaos.2020.110086

Abstract

Discussions about the recently identified deadly coronavirus disease (COVID-19) which originated in Wuhan, China in December 2019 are common around the globe now. This is an infectious and even life-threatening disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has rapidly spread to other countries from its originating place infecting millions of people globally. To understand future phenomena, strong mathematical models are required with the least prediction errors. In the present study, autoregressive integrated moving average (ARIMA) and least square support vector machine (LS-SVM) models are applied to the data consisting of daily confirmed cases of SARS-CoV-2 in the most affected five countries of the world for modeling and predicting one-month confirmed cases of this disease. To validate these models, the prediction results were tested by comparing it with testing data. The results revealed better accuracy of the LS-SVM model over the ARIMA model and also suggested a rapid rise of SARS-CoV-2 confirmed cases in all the countries under study. This analysis would help governments to take necessary actions in advance associated with the preparation of isolation wards, availability of medicines and medical staff, a decision on lockdown, training of volunteers, and economic plans.

Keywords: ARIMA model; Least square support vector machine; Prediction; SARS-COV-2 cases.

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Conflict of interest statement

Authors have no conflict of interest.

Figures

Fig 1 — **Fig. 1**
Time series plot of COVID-19 cases from Five countries.

Fig 2 — **Fig. 2**
Flow charts for modeling and forecasting of COVID-19 confirmed cases data using (a) ARIMA model (b) LS-SVM model.

Fig 3 — **Fig. 3**
Comparison of ARIMA and LS-SVM models forecast of COVID-19 confirmed cases for the testing phase of the countries (i & ii) France (iii & iv) Italy (v & vi) Spain (vii & viii) UK and (ix & x) USA.

Fig 4 — **Fig. 4**
One month ahead of COVID-19 affected cases in different countries by the ARIMA model.

Fig 5 — **Fig. 5**
One month ahead, COVID-19 affected cases in different countries by LS-SVM.

See this image and copyright information in PMC

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References

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[1] Abdirizak F., Lewis R., Chowell G. “Evaluating the potential impact of targeted vaccination strategies against severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) outbreaks in the healthcare setting. Theor Biol Med Model. 2019;16(1):16. - PMC - PubMed

[2] Abdirizak F., Lewis R., Chowell G. “Evaluating the potential impact of targeted vaccination strategies against severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV) outbreaks in the healthcare setting. Theor Biol Med Model. 2019;16(1):16. - PMC - PubMed

[3] Aladaga C.H., Egrioglub E., Kadilar C. “Forecasting non-linear time series with a hybrid methodology. Appl Math Lett. 2009;22(9):1467–1470.

[4] Aladaga C.H., Egrioglub E., Kadilar C. “Forecasting non-linear time series with a hybrid methodology. Appl Math Lett. 2009;22(9):1467–1470.

[5] Binti Hamzah F.A., Lau C., Nazri H., Ligot D.V., Lee G., Tan C.L., et al. CoronaTracker: worldwide COVID-19 outbreak data analysis and prediction. Bull World Health Organ. 2020 doi: 10.2471/BLT.20.255695. [Submitted]. - DOI

[6] Binti Hamzah F.A., Lau C., Nazri H., Ligot D.V., Lee G., Tan C.L., et al. CoronaTracker: worldwide COVID-19 outbreak data analysis and prediction. Bull World Health Organ. 2020 doi: 10.2471/BLT.20.255695. [Submitted]. - DOI

[7] Box G.E.P., Jenkins G.M. Holden Day; San Francisco, CA: 1976. Time series analysis, forecasting and control.

[8] Box G.E.P., Jenkins G.M. Holden Day; San Francisco, CA: 1976. Time series analysis, forecasting and control.

[9] Brockwell P.J., Davis R.A. Springer Texts in Statistics; 2002. Introduction to time series and forecasting.

[10] Brockwell P.J., Davis R.A. Springer Texts in Statistics; 2002. Introduction to time series and forecasting.

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Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries

Affiliations

Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries

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Affiliations

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Conflict of interest statement

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