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A Statistical Modeling of the Course of COVID-19 (SARS-CoV-2) Outbreak: A Comparative Analysis

This study aims to provide both a model by using cumulative cases and cumulative death toll for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) outbreak in four countries, China, Italy, South Korea, and Turkey, starting from the first diagnosis and to compare associated indicators. The...

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Autores principales: Ankarali, Handan, Ankarali, Seyit, Caskurlu, Hulya, Cag, Yasemin, Arslan, Ferhat, Erdem, Hakan, Vahaboglu, Haluk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251623/
https://www.ncbi.nlm.nih.gov/pubmed/32450712
http://dx.doi.org/10.1177/1010539520928180
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author Ankarali, Handan
Ankarali, Seyit
Caskurlu, Hulya
Cag, Yasemin
Arslan, Ferhat
Erdem, Hakan
Vahaboglu, Haluk
author_facet Ankarali, Handan
Ankarali, Seyit
Caskurlu, Hulya
Cag, Yasemin
Arslan, Ferhat
Erdem, Hakan
Vahaboglu, Haluk
author_sort Ankarali, Handan
collection PubMed
description This study aims to provide both a model by using cumulative cases and cumulative death toll for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) outbreak in four countries, China, Italy, South Korea, and Turkey, starting from the first diagnosis and to compare associated indicators. The most successful estimation was obtained from the cubic model with natural logarithm for China, Italy, South Korea, and Turkey. The success of the models was around 99%. However, differences began to emerge in China, Italy, and South Korea after the second week. Although the highest number of new cases per 1 million people in China was 9.8 on February 28, 2020; it was 108.4 on March 21, 2020, in Italy; and this was 16.6 on March 5, 2020, in South Korea. On the other hand, the number of new cases was 24.6 per 1 million people on March 27, 2020, in Turkey. The log-cubic model proposed in this study has been set forth to obtain successful results for aforementioned countries, as well as to estimate the course of the COVID-19 outbreak. Other factors such as climacteric factors and genetic differences, which may have an impact on viral spreading and transmission, would also have strengthened the model prediction capacity.
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spelling pubmed-72516232020-05-27 A Statistical Modeling of the Course of COVID-19 (SARS-CoV-2) Outbreak: A Comparative Analysis Ankarali, Handan Ankarali, Seyit Caskurlu, Hulya Cag, Yasemin Arslan, Ferhat Erdem, Hakan Vahaboglu, Haluk Asia Pac J Public Health COVID Articles This study aims to provide both a model by using cumulative cases and cumulative death toll for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) outbreak in four countries, China, Italy, South Korea, and Turkey, starting from the first diagnosis and to compare associated indicators. The most successful estimation was obtained from the cubic model with natural logarithm for China, Italy, South Korea, and Turkey. The success of the models was around 99%. However, differences began to emerge in China, Italy, and South Korea after the second week. Although the highest number of new cases per 1 million people in China was 9.8 on February 28, 2020; it was 108.4 on March 21, 2020, in Italy; and this was 16.6 on March 5, 2020, in South Korea. On the other hand, the number of new cases was 24.6 per 1 million people on March 27, 2020, in Turkey. The log-cubic model proposed in this study has been set forth to obtain successful results for aforementioned countries, as well as to estimate the course of the COVID-19 outbreak. Other factors such as climacteric factors and genetic differences, which may have an impact on viral spreading and transmission, would also have strengthened the model prediction capacity. SAGE Publications 2020-05-25 2020-05 /pmc/articles/PMC7251623/ /pubmed/32450712 http://dx.doi.org/10.1177/1010539520928180 Text en © 2020 APJPH https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle COVID Articles
Ankarali, Handan
Ankarali, Seyit
Caskurlu, Hulya
Cag, Yasemin
Arslan, Ferhat
Erdem, Hakan
Vahaboglu, Haluk
A Statistical Modeling of the Course of COVID-19 (SARS-CoV-2) Outbreak: A Comparative Analysis
title A Statistical Modeling of the Course of COVID-19 (SARS-CoV-2) Outbreak: A Comparative Analysis
title_full A Statistical Modeling of the Course of COVID-19 (SARS-CoV-2) Outbreak: A Comparative Analysis
title_fullStr A Statistical Modeling of the Course of COVID-19 (SARS-CoV-2) Outbreak: A Comparative Analysis
title_full_unstemmed A Statistical Modeling of the Course of COVID-19 (SARS-CoV-2) Outbreak: A Comparative Analysis
title_short A Statistical Modeling of the Course of COVID-19 (SARS-CoV-2) Outbreak: A Comparative Analysis
title_sort statistical modeling of the course of covid-19 (sars-cov-2) outbreak: a comparative analysis
topic COVID Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7251623/
https://www.ncbi.nlm.nih.gov/pubmed/32450712
http://dx.doi.org/10.1177/1010539520928180
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