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Association of Environmental Parameters with COVID-19 in Delhi, India
The present study explores the association between weather and COVID-19 pandemic in Delhi, India. The study used the data from daily newspaper releases from the Ministry of Health and Family Welfare, Government of India. Linear regression was run to understand the effect of the number of tests, temp...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer India
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436072/ https://www.ncbi.nlm.nih.gov/pubmed/32837037 http://dx.doi.org/10.1007/s12291-020-00921-6 |
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author | Ladha, Nikhilesh Bhardwaj, Pankaj Charan, Jaykaran Mitra, Prasenjit Goyal, Jagdish Prasad Sharma, Praveen Singh, Kuldeep Misra, Sanjeev |
author_facet | Ladha, Nikhilesh Bhardwaj, Pankaj Charan, Jaykaran Mitra, Prasenjit Goyal, Jagdish Prasad Sharma, Praveen Singh, Kuldeep Misra, Sanjeev |
author_sort | Ladha, Nikhilesh |
collection | PubMed |
description | The present study explores the association between weather and COVID-19 pandemic in Delhi, India. The study used the data from daily newspaper releases from the Ministry of Health and Family Welfare, Government of India. Linear regression was run to understand the effect of the number of tests, temperature, and relative humidity on the number of COVID-19 cases in Delhi. The model was significantly able to predict number of COVID-19 cases, F (4,56) = 1213.61, p < 0.05, accounting for 99.4% of the variation in COVID-19 cases with adjusted R(2) = 98.8%. Maximum Temperature, average temperature and average relative humidity did not show statistical significance. The only number of tests was significantly associated with COVID-19 cases. |
format | Online Article Text |
id | pubmed-7436072 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-74360722020-08-19 Association of Environmental Parameters with COVID-19 in Delhi, India Ladha, Nikhilesh Bhardwaj, Pankaj Charan, Jaykaran Mitra, Prasenjit Goyal, Jagdish Prasad Sharma, Praveen Singh, Kuldeep Misra, Sanjeev Indian J Clin Biochem Short Communication The present study explores the association between weather and COVID-19 pandemic in Delhi, India. The study used the data from daily newspaper releases from the Ministry of Health and Family Welfare, Government of India. Linear regression was run to understand the effect of the number of tests, temperature, and relative humidity on the number of COVID-19 cases in Delhi. The model was significantly able to predict number of COVID-19 cases, F (4,56) = 1213.61, p < 0.05, accounting for 99.4% of the variation in COVID-19 cases with adjusted R(2) = 98.8%. Maximum Temperature, average temperature and average relative humidity did not show statistical significance. The only number of tests was significantly associated with COVID-19 cases. Springer India 2020-08-19 2020-10 /pmc/articles/PMC7436072/ /pubmed/32837037 http://dx.doi.org/10.1007/s12291-020-00921-6 Text en © Association of Clinical Biochemists of India 2020 |
spellingShingle | Short Communication Ladha, Nikhilesh Bhardwaj, Pankaj Charan, Jaykaran Mitra, Prasenjit Goyal, Jagdish Prasad Sharma, Praveen Singh, Kuldeep Misra, Sanjeev Association of Environmental Parameters with COVID-19 in Delhi, India |
title | Association of Environmental Parameters with COVID-19 in Delhi, India |
title_full | Association of Environmental Parameters with COVID-19 in Delhi, India |
title_fullStr | Association of Environmental Parameters with COVID-19 in Delhi, India |
title_full_unstemmed | Association of Environmental Parameters with COVID-19 in Delhi, India |
title_short | Association of Environmental Parameters with COVID-19 in Delhi, India |
title_sort | association of environmental parameters with covid-19 in delhi, india |
topic | Short Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7436072/ https://www.ncbi.nlm.nih.gov/pubmed/32837037 http://dx.doi.org/10.1007/s12291-020-00921-6 |
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