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Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach
Undeniably, the Novel Coronavirus 2019, (COVID-19), has disrupted the routine functioning of the global economic and social activities. In particular, vulnerable economies such as the Small Island Developing states (SIDs) are facing unprecedented health and financial crisis. In such critical situati...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775656/ http://dx.doi.org/10.1016/j.aej.2020.12.047 |
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author | Mamode Khan, Naushad Bakouch, Hassan S. Soobhug, Ashwinee Devi Scotto, Manuel G. |
author_facet | Mamode Khan, Naushad Bakouch, Hassan S. Soobhug, Ashwinee Devi Scotto, Manuel G. |
author_sort | Mamode Khan, Naushad |
collection | PubMed |
description | Undeniably, the Novel Coronavirus 2019, (COVID-19), has disrupted the routine functioning of the global economic and social activities. In particular, vulnerable economies such as the Small Island Developing states (SIDs) are facing unprecedented health and financial crisis. In such critical situation, some in-depth statistical models can be helpful for proper planning in terms of identifying factors that can influence significantly the number of infected COVID-19 cases and for forecasting. Modelling the COVID-19 infected series is a statistical challenge since the series are severely over-dispersed with lots of oscillations. This paper attempts a new integer-valued time series model based on the auto-regressive structure (INAR), with an oscillating Weighted Cosine Geometric (WCG) innovation term. The parameters in the proposed model constitute of the regression effects and serial auto-correlation coefficients and are estimated via likelihood and moment-based approaches. Monte Carlo simulation experiments are implemented to assess the performance and consistency of the different resulting estimators. Thereon, the INAR-WCG is applied to the COVID-19 series of various SIDs countries that include Singapore, Cape Verde, Bahrain, Mauritius and Maldives. The findings reveal that factors such as the transmission mode and the Government Stringency Index are the most influential. In terms of model fitting and forecasting, the INAR-WCG provides slightly better RMSEs than the other competing INAR-based processes. |
format | Online Article Text |
id | pubmed-7775656 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. |
record_format | MEDLINE/PubMed |
spelling | pubmed-77756562021-01-04 Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach Mamode Khan, Naushad Bakouch, Hassan S. Soobhug, Ashwinee Devi Scotto, Manuel G. Alexandria Engineering Journal Article Undeniably, the Novel Coronavirus 2019, (COVID-19), has disrupted the routine functioning of the global economic and social activities. In particular, vulnerable economies such as the Small Island Developing states (SIDs) are facing unprecedented health and financial crisis. In such critical situation, some in-depth statistical models can be helpful for proper planning in terms of identifying factors that can influence significantly the number of infected COVID-19 cases and for forecasting. Modelling the COVID-19 infected series is a statistical challenge since the series are severely over-dispersed with lots of oscillations. This paper attempts a new integer-valued time series model based on the auto-regressive structure (INAR), with an oscillating Weighted Cosine Geometric (WCG) innovation term. The parameters in the proposed model constitute of the regression effects and serial auto-correlation coefficients and are estimated via likelihood and moment-based approaches. Monte Carlo simulation experiments are implemented to assess the performance and consistency of the different resulting estimators. Thereon, the INAR-WCG is applied to the COVID-19 series of various SIDs countries that include Singapore, Cape Verde, Bahrain, Mauritius and Maldives. The findings reveal that factors such as the transmission mode and the Government Stringency Index are the most influential. In terms of model fitting and forecasting, the INAR-WCG provides slightly better RMSEs than the other competing INAR-based processes. THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. 2021-04 2021-01-01 /pmc/articles/PMC7775656/ http://dx.doi.org/10.1016/j.aej.2020.12.047 Text en © 2020 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Mamode Khan, Naushad Bakouch, Hassan S. Soobhug, Ashwinee Devi Scotto, Manuel G. Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach |
title | Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach |
title_full | Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach |
title_fullStr | Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach |
title_full_unstemmed | Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach |
title_short | Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach |
title_sort | insights on the trend of the novel coronavirus 2019 series in some small island developing states: a thinning-based modelling approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775656/ http://dx.doi.org/10.1016/j.aej.2020.12.047 |
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