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Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India
The novel coronavirus disease is known as COVID-19, which is declared as a pandemic by the World Health Organization during March 2020. In this study, the COVID-19 connection with various weather parameters like temperature, wind speed, and relative humidity is investigated and the future scenario o...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515685/ https://www.ncbi.nlm.nih.gov/pubmed/32994752 http://dx.doi.org/10.1007/s10668-020-01000-9 |
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author | Awasthi, Amit Sharma, Aditi Kaur, Prabhjot Gugamsetty, Balakrishnaiah Kumar, Akshay |
author_facet | Awasthi, Amit Sharma, Aditi Kaur, Prabhjot Gugamsetty, Balakrishnaiah Kumar, Akshay |
author_sort | Awasthi, Amit |
collection | PubMed |
description | The novel coronavirus disease is known as COVID-19, which is declared as a pandemic by the World Health Organization during March 2020. In this study, the COVID-19 connection with various weather parameters like temperature, wind speed, and relative humidity is investigated and the future scenario of COVID-19 is predicted based on the Gaussian model (GM). This study is conducted in Delhi, the capital city of India, during the lowest mobility rate due to strict lockdown nationwide for about two months from March 15 to May 17, 2020. Spearman correlation is applied to obtain the interconnection of COVID-19 cases with weather parameters. Based on statistical analysis, this has been observed that the temperature parameter shows a significant positive trend during the period of study. The number of confirmed cases of COVID-19 is fitted with respect to the number of days by using the Gaussian curve and it is estimated on the basis of the model that maximum cases will go up to 123,886 in number. The maximum number of cases will be observed during the range of 166 ± 36 days. It is also estimated by using the width of the fitted GM that it will take minimum of 10 months for the complete recovery from COVID-19. Additionally, the linear regression technique is used to find the trend of COVID-19 cases with temperature and it is estimated that with an increase in temperature by 1 °C, 30 new COVID-19 cases on daily basis will be expected to observe. This study is believed to be a preliminary study and to better understand the concrete relationship of coronavirus, at least one complete cycle is essential to investigate. The laboratory-based study is essential to be done to support the present field-based study. Henceforth, based on preliminary studies, significant inputs are put forth to the research community and government to formulate thoughtful strategies like medical facilities such as ventilators, beds, testing centers, quarantine centers, etc., to curb the effects of COVID-19. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10668-020-01000-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7515685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-75156852020-09-25 Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India Awasthi, Amit Sharma, Aditi Kaur, Prabhjot Gugamsetty, Balakrishnaiah Kumar, Akshay Environ Dev Sustain Review The novel coronavirus disease is known as COVID-19, which is declared as a pandemic by the World Health Organization during March 2020. In this study, the COVID-19 connection with various weather parameters like temperature, wind speed, and relative humidity is investigated and the future scenario of COVID-19 is predicted based on the Gaussian model (GM). This study is conducted in Delhi, the capital city of India, during the lowest mobility rate due to strict lockdown nationwide for about two months from March 15 to May 17, 2020. Spearman correlation is applied to obtain the interconnection of COVID-19 cases with weather parameters. Based on statistical analysis, this has been observed that the temperature parameter shows a significant positive trend during the period of study. The number of confirmed cases of COVID-19 is fitted with respect to the number of days by using the Gaussian curve and it is estimated on the basis of the model that maximum cases will go up to 123,886 in number. The maximum number of cases will be observed during the range of 166 ± 36 days. It is also estimated by using the width of the fitted GM that it will take minimum of 10 months for the complete recovery from COVID-19. Additionally, the linear regression technique is used to find the trend of COVID-19 cases with temperature and it is estimated that with an increase in temperature by 1 °C, 30 new COVID-19 cases on daily basis will be expected to observe. This study is believed to be a preliminary study and to better understand the concrete relationship of coronavirus, at least one complete cycle is essential to investigate. The laboratory-based study is essential to be done to support the present field-based study. Henceforth, based on preliminary studies, significant inputs are put forth to the research community and government to formulate thoughtful strategies like medical facilities such as ventilators, beds, testing centers, quarantine centers, etc., to curb the effects of COVID-19. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10668-020-01000-9) contains supplementary material, which is available to authorized users. Springer Netherlands 2020-09-25 2021 /pmc/articles/PMC7515685/ /pubmed/32994752 http://dx.doi.org/10.1007/s10668-020-01000-9 Text en © Springer Nature B.V. 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Review Awasthi, Amit Sharma, Aditi Kaur, Prabhjot Gugamsetty, Balakrishnaiah Kumar, Akshay Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India |
title | Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India |
title_full | Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India |
title_fullStr | Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India |
title_full_unstemmed | Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India |
title_short | Statistical interpretation of environmental influencing parameters on COVID-19 during the lockdown in Delhi, India |
title_sort | statistical interpretation of environmental influencing parameters on covid-19 during the lockdown in delhi, india |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515685/ https://www.ncbi.nlm.nih.gov/pubmed/32994752 http://dx.doi.org/10.1007/s10668-020-01000-9 |
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