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New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors
BACKGROUND: World Health Organization has reported fifty countries have now detected the new coronavirus (B.1.1.7 variant) since a couple of months ago. In Indonesia, the B.1.1.7 cases have been found in several provinces since January 2021, although they are still in a lower number than the old var...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8180350/ https://www.ncbi.nlm.nih.gov/pubmed/34175236 http://dx.doi.org/10.1016/j.jiph.2021.05.019 |
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author | Rendana, Muhammad Idris, Wan Mohd Razi |
author_facet | Rendana, Muhammad Idris, Wan Mohd Razi |
author_sort | Rendana, Muhammad |
collection | PubMed |
description | BACKGROUND: World Health Organization has reported fifty countries have now detected the new coronavirus (B.1.1.7 variant) since a couple of months ago. In Indonesia, the B.1.1.7 cases have been found in several provinces since January 2021, although they are still in a lower number than the old variant of COVID-19. Therefore, this study aims to create a forecast analysis regarding the occasions of COVID-19 and B.1.1.7 cases based on data from the 1st January to 18th March 2021, and also analyze the association between meteorological factors with B.1.1.7 incidences in three different provinces of Indonesia such as the West Java, South Sumatra and East Kalimantan. METHODS: We used the Autoregressive Moving Average Models (ARIMA) to forecast the number of cases in the upcoming 14 days and the Spearman correlation analysis to analyze the relationship between B.1.1.7 cases and meteorological variables such as temperature, humidity, rainfall, sunshine, and wind speed. RESULTS: The results of the study showed the fitted ARIMA models forecasted there was an increase in the daily cases in three provinces. The total cases in three provinces would increase by 36% (West Java), 13.5% (South Sumatra), and 30% (East Kalimantan) as compared with actual cases until the end of 14 days later. The temperature, rainfall and sunshine factors were the main contributors for B.1.1.7 cases with each correlation coefficients; r = −0.230; p < 0.05, r = 0.211; p < 0.05 and r = −0.418; p < 0.01, respectively. CONCLUSIONS: We recapitulated that this investigation was the first preliminary study to analyze a short-term forecast regarding COVID-19 and B.1.1.7 cases as well as to determine the associated meteorological factors that become primary contributors to the virus spread. |
format | Online Article Text |
id | pubmed-8180350 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Authors. Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81803502021-06-07 New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors Rendana, Muhammad Idris, Wan Mohd Razi J Infect Public Health Article BACKGROUND: World Health Organization has reported fifty countries have now detected the new coronavirus (B.1.1.7 variant) since a couple of months ago. In Indonesia, the B.1.1.7 cases have been found in several provinces since January 2021, although they are still in a lower number than the old variant of COVID-19. Therefore, this study aims to create a forecast analysis regarding the occasions of COVID-19 and B.1.1.7 cases based on data from the 1st January to 18th March 2021, and also analyze the association between meteorological factors with B.1.1.7 incidences in three different provinces of Indonesia such as the West Java, South Sumatra and East Kalimantan. METHODS: We used the Autoregressive Moving Average Models (ARIMA) to forecast the number of cases in the upcoming 14 days and the Spearman correlation analysis to analyze the relationship between B.1.1.7 cases and meteorological variables such as temperature, humidity, rainfall, sunshine, and wind speed. RESULTS: The results of the study showed the fitted ARIMA models forecasted there was an increase in the daily cases in three provinces. The total cases in three provinces would increase by 36% (West Java), 13.5% (South Sumatra), and 30% (East Kalimantan) as compared with actual cases until the end of 14 days later. The temperature, rainfall and sunshine factors were the main contributors for B.1.1.7 cases with each correlation coefficients; r = −0.230; p < 0.05, r = 0.211; p < 0.05 and r = −0.418; p < 0.01, respectively. CONCLUSIONS: We recapitulated that this investigation was the first preliminary study to analyze a short-term forecast regarding COVID-19 and B.1.1.7 cases as well as to determine the associated meteorological factors that become primary contributors to the virus spread. The Authors. Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2021-10 2021-06-06 /pmc/articles/PMC8180350/ /pubmed/34175236 http://dx.doi.org/10.1016/j.jiph.2021.05.019 Text en © 2021 The Authors 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 Rendana, Muhammad Idris, Wan Mohd Razi New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors |
title | New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors |
title_full | New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors |
title_fullStr | New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors |
title_full_unstemmed | New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors |
title_short | New COVID-19 variant (B.1.1.7): Forecasting the occasion of virus and the related meteorological factors |
title_sort | new covid-19 variant (b.1.1.7): forecasting the occasion of virus and the related meteorological factors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8180350/ https://www.ncbi.nlm.nih.gov/pubmed/34175236 http://dx.doi.org/10.1016/j.jiph.2021.05.019 |
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