Research Article

Analyzing the trend in COVID-19 data: The structural break approach

Volume: 14 Number: 3 March 2, 2023
EN

Analyzing the trend in COVID-19 data: The structural break approach

Abstract

In this paper, we have considered three important variables concerning COVID-19 viz., (i) the number of daily new cases, (ii) the number of daily total cases, and (iii) the number of daily deaths, and proposed a modelling procedure, so that the nature of trend in these series could be studied appropriately and then used for identifying the current phase of the pandemic including the phase of containment, if happening /happened, in any country. The proposed modelling procedure gives due consideration to structural breaks in the series. The data from four countries, Brazil, India, Italy and the UK, have been used to study the efficacy of the proposed model. Regarding the phase of infection in these countries, we have found, using data till 19 May 2020, that both Brazil and India are in the increasing phase with infections rising up and further up, but Italy and the UK are in decreasing/containing phase suggesting that these two countries are expected to be free of this pandemic in due course of time provided their respective trend continues. The forecast performance of this model has also established its superiority, as compared to two other standard trend models viz., polynomial and exponential trend models.

Keywords

Thanks

We are grateful to Professor Mohitosh Kejriwal for providing us with the GAUSS code of the Kejriwal and Perron (2010) test.

References

  1. [1] Coronavirus disease 2019 (COVID-19): situation report, 72. World Health Organization 2020.
  2. [2] Wu JT, Leung K, Leung GM. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. The Lancet 2020;395:689-97.
  3. [3] Calafiore GC, Novara C, Possieri C. A modified sir model for the covid-19 contagion in italy. arXiv preprint arXiv:200314391 2020.
  4. [4] Kucharski AJ, Russell TW, Diamond C, Liu Y, Edmunds J, Funk S, et al. Early dynamics of transmission and control of COVID-19: a mathematical modelling study. The lancet infectious diseases 2020.
  5. [5] Simha A, Prasad RV, Narayana S. A simple stochastic sir model for covid 19 infection dynamics for karnataka: Learning from europe. arXiv preprint arXiv:200311920 2020.
  6. [6] Anastassopoulou C, Russo L, Tsakris A, Siettos C. Data-based analysis, modelling and forecasting of the novel coronavirus (2019-Ncov) outbreak. medRxiv 2020.
  7. [7] Nesteruk I. Statistics-based predictions of coronavirus epidemic spreading in mainland China. 2020.
  8. [8] Nabi KN. Forecasting COVID-19 Pandemic: A Data-Driven Analysis. Chaos, Solitons & Fractals 2020:110046.

Details

Primary Language

English

Subjects

Economics

Journal Section

Research Article

Publication Date

March 2, 2023

Submission Date

March 2, 2021

Acceptance Date

February 27, 2023

Published in Issue

Year 2022 Volume: 14 Number: 3

APA
Sarkar, N., & Banik Chowdhury, K. (2023). Analyzing the trend in COVID-19 data: The structural break approach. International Econometric Review, 14(3), 72-96. https://doi.org/10.33818/ier.889467
AMA
1.Sarkar N, Banik Chowdhury K. Analyzing the trend in COVID-19 data: The structural break approach. IER. 2023;14(3):72-96. doi:10.33818/ier.889467
Chicago
Sarkar, Nityananda, and Kushal Banik Chowdhury. 2023. “Analyzing the Trend in COVID-19 Data: The Structural Break Approach”. International Econometric Review 14 (3): 72-96. https://doi.org/10.33818/ier.889467.
EndNote
Sarkar N, Banik Chowdhury K (March 1, 2023) Analyzing the trend in COVID-19 data: The structural break approach. International Econometric Review 14 3 72–96.
IEEE
[1]N. Sarkar and K. Banik Chowdhury, “Analyzing the trend in COVID-19 data: The structural break approach”, IER, vol. 14, no. 3, pp. 72–96, Mar. 2023, doi: 10.33818/ier.889467.
ISNAD
Sarkar, Nityananda - Banik Chowdhury, Kushal. “Analyzing the Trend in COVID-19 Data: The Structural Break Approach”. International Econometric Review 14/3 (March 1, 2023): 72-96. https://doi.org/10.33818/ier.889467.
JAMA
1.Sarkar N, Banik Chowdhury K. Analyzing the trend in COVID-19 data: The structural break approach. IER. 2023;14:72–96.
MLA
Sarkar, Nityananda, and Kushal Banik Chowdhury. “Analyzing the Trend in COVID-19 Data: The Structural Break Approach”. International Econometric Review, vol. 14, no. 3, Mar. 2023, pp. 72-96, doi:10.33818/ier.889467.
Vancouver
1.Nityananda Sarkar, Kushal Banik Chowdhury. Analyzing the trend in COVID-19 data: The structural break approach. IER. 2023 Mar. 1;14(3):72-96. doi:10.33818/ier.889467