Coronavirus, also known as COVID-19 was first originated in Wuhan, Hubei province in China around December 2019 andspread out all over the world within few weeks. Following the outbreak, the World Health Organization (WHO) declares the outbreak as pandemic on 11 March 2019. The coronavirus (COVID-19) have a fast transmission nature and grow exponentially across the globe. Subsequently, to model the exponential growing nature of the virus, different researchers conducted their study using a linear based time series (such as ARMA family) models. However, such linear time series models cannot handle data having an exponential growing pattern. Since linear based time series models cannot handle a data having an exponential growing pattern, we applied the common exponential family models such as an Exponential Growth Model, Simple Exponential Smoothing (SES), and Double Exponential Smoothing (DES) methods in Ethiopia from March 14, 2020 to June 05, 2020. The results of the study showed that double exponential smoothing methods was appropriate in forecasting the future number of COVID-19 cases in Ethiopia as dictated by lowest value of root mean sum of square error. The forecasting model shows that the number of coronavirus cases in Ethiopia grows exponentially. In general, the forecast helps the Ethiopian government, policy makers, and the society at all to take preventive measures before the transmission become out of control especially rural areas since until now, most of the cases were observed in urban areas.
| Published in | International Journal of Biomedical Engineering and Clinical Science (Volume 7, Issue 1) |
| DOI | 10.11648/j.ijbecs.20210701.11 |
| Page(s) | 1-6 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2021. Published by Science Publishing Group |
Coronavirus, COVID-19, Exponential Smoothing Model, Forecasting, RMSSE
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APA Style
Teshome Hailemeskel Abebe. (2021). Forecasting the Number of Coronavirus (COVID-19) Cases in Ethiopia Using Exponential Smoothing Times Series Model. International Journal of Biomedical Engineering and Clinical Science, 7(1), 1-6. https://doi.org/10.11648/j.ijbecs.20210701.11
ACS Style
Teshome Hailemeskel Abebe. Forecasting the Number of Coronavirus (COVID-19) Cases in Ethiopia Using Exponential Smoothing Times Series Model. Int. J. Biomed. Eng. Clin. Sci. 2021, 7(1), 1-6. doi: 10.11648/j.ijbecs.20210701.11
AMA Style
Teshome Hailemeskel Abebe. Forecasting the Number of Coronavirus (COVID-19) Cases in Ethiopia Using Exponential Smoothing Times Series Model. Int J Biomed Eng Clin Sci. 2021;7(1):1-6. doi: 10.11648/j.ijbecs.20210701.11
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Download@article{10.11648/j.ijbecs.20210701.11,
author = {Teshome Hailemeskel Abebe},
title = {Forecasting the Number of Coronavirus (COVID-19) Cases in Ethiopia Using Exponential Smoothing Times Series Model},
journal = {International Journal of Biomedical Engineering and Clinical Science},
volume = {7},
number = {1},
pages = {1-6},
doi = {10.11648/j.ijbecs.20210701.11},
url = {https://doi.org/10.11648/j.ijbecs.20210701.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijbecs.20210701.11},
abstract = {Coronavirus, also known as COVID-19 was first originated in Wuhan, Hubei province in China around December 2019 andspread out all over the world within few weeks. Following the outbreak, the World Health Organization (WHO) declares the outbreak as pandemic on 11 March 2019. The coronavirus (COVID-19) have a fast transmission nature and grow exponentially across the globe. Subsequently, to model the exponential growing nature of the virus, different researchers conducted their study using a linear based time series (such as ARMA family) models. However, such linear time series models cannot handle data having an exponential growing pattern. Since linear based time series models cannot handle a data having an exponential growing pattern, we applied the common exponential family models such as an Exponential Growth Model, Simple Exponential Smoothing (SES), and Double Exponential Smoothing (DES) methods in Ethiopia from March 14, 2020 to June 05, 2020. The results of the study showed that double exponential smoothing methods was appropriate in forecasting the future number of COVID-19 cases in Ethiopia as dictated by lowest value of root mean sum of square error. The forecasting model shows that the number of coronavirus cases in Ethiopia grows exponentially. In general, the forecast helps the Ethiopian government, policy makers, and the society at all to take preventive measures before the transmission become out of control especially rural areas since until now, most of the cases were observed in urban areas.},
year = {2021}
}
TY - JOUR T1 - Forecasting the Number of Coronavirus (COVID-19) Cases in Ethiopia Using Exponential Smoothing Times Series Model AU - Teshome Hailemeskel Abebe Y1 - 2021/03/04 PY - 2021 N1 - https://doi.org/10.11648/j.ijbecs.20210701.11 DO - 10.11648/j.ijbecs.20210701.11 T2 - International Journal of Biomedical Engineering and Clinical Science JF - International Journal of Biomedical Engineering and Clinical Science JO - International Journal of Biomedical Engineering and Clinical Science SP - 1 EP - 6 PB - Science Publishing Group SN - 2472-1301 UR - https://doi.org/10.11648/j.ijbecs.20210701.11 AB - Coronavirus, also known as COVID-19 was first originated in Wuhan, Hubei province in China around December 2019 andspread out all over the world within few weeks. Following the outbreak, the World Health Organization (WHO) declares the outbreak as pandemic on 11 March 2019. The coronavirus (COVID-19) have a fast transmission nature and grow exponentially across the globe. Subsequently, to model the exponential growing nature of the virus, different researchers conducted their study using a linear based time series (such as ARMA family) models. However, such linear time series models cannot handle data having an exponential growing pattern. Since linear based time series models cannot handle a data having an exponential growing pattern, we applied the common exponential family models such as an Exponential Growth Model, Simple Exponential Smoothing (SES), and Double Exponential Smoothing (DES) methods in Ethiopia from March 14, 2020 to June 05, 2020. The results of the study showed that double exponential smoothing methods was appropriate in forecasting the future number of COVID-19 cases in Ethiopia as dictated by lowest value of root mean sum of square error. The forecasting model shows that the number of coronavirus cases in Ethiopia grows exponentially. In general, the forecast helps the Ethiopian government, policy makers, and the society at all to take preventive measures before the transmission become out of control especially rural areas since until now, most of the cases were observed in urban areas. VL - 7 IS - 1 ER -