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Multiple change point estimation of trends in Covid-19 infections and deaths in India as compared with WHO regions
The present study aims at estimating the multiple change points for the time series data of COVID-19 confirmed cases and deaths and trend estimation within the estimated multiple change points (MCP) in India as compared with WHO regions. The data were described using descriptive statistical measures...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413104/ https://www.ncbi.nlm.nih.gov/pubmed/34493970 http://dx.doi.org/10.1016/j.spasta.2021.100538 |
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author | S.T., Pavan Kumar Lahiri, Biswajit Alvarado, Rafael |
author_facet | S.T., Pavan Kumar Lahiri, Biswajit Alvarado, Rafael |
author_sort | S.T., Pavan Kumar |
collection | PubMed |
description | The present study aims at estimating the multiple change points for the time series data of COVID-19 confirmed cases and deaths and trend estimation within the estimated multiple change points (MCP) in India as compared with WHO regions. The data were described using descriptive statistical measures, and for the estimation of change point’s E-divisive procedure was employed. Further, the trend within the estimated change points was tested using Sen’s slope and Mann Kendal tests. India, along with the African Region, American region, and South East Asia regions experienced a significant surge in the fresh cases up to the 5th Change point. Among the WHO regions, The American region was the worst hit by the pandemic in case of fresh cases and deaths. While the European region experienced an early negative trend of fresh cases during the 3rd and 4th change point, but later the situation reversed by the 5th (7th July 2020) and 6th (6th August 2020) change point. The trend of deaths in India and the South-East Asia Region was similar, and global deaths had a negative trend from the 4th (17th May 2020) Change point onwards. The change points were estimated with prefixed significance level [Formula: see text] < 0.002. Infections and deaths were positively significant for India and SEARO region across change points. Infection was significant at every 30 days interval across other WHO regions, and any delay in the infections was due to the interventions. The European region is expected to have a second wave of positive infections during the 5th and 6th change points though the early two change points were negatively significant. The study highlights the efficacy of change point analysis in understanding the dynamics of covid-19 cases in India and across the world. It further helps to develop effective public health strategies. |
format | Online Article Text |
id | pubmed-8413104 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84131042021-09-03 Multiple change point estimation of trends in Covid-19 infections and deaths in India as compared with WHO regions S.T., Pavan Kumar Lahiri, Biswajit Alvarado, Rafael Spat Stat Article The present study aims at estimating the multiple change points for the time series data of COVID-19 confirmed cases and deaths and trend estimation within the estimated multiple change points (MCP) in India as compared with WHO regions. The data were described using descriptive statistical measures, and for the estimation of change point’s E-divisive procedure was employed. Further, the trend within the estimated change points was tested using Sen’s slope and Mann Kendal tests. India, along with the African Region, American region, and South East Asia regions experienced a significant surge in the fresh cases up to the 5th Change point. Among the WHO regions, The American region was the worst hit by the pandemic in case of fresh cases and deaths. While the European region experienced an early negative trend of fresh cases during the 3rd and 4th change point, but later the situation reversed by the 5th (7th July 2020) and 6th (6th August 2020) change point. The trend of deaths in India and the South-East Asia Region was similar, and global deaths had a negative trend from the 4th (17th May 2020) Change point onwards. The change points were estimated with prefixed significance level [Formula: see text] < 0.002. Infections and deaths were positively significant for India and SEARO region across change points. Infection was significant at every 30 days interval across other WHO regions, and any delay in the infections was due to the interventions. The European region is expected to have a second wave of positive infections during the 5th and 6th change points though the early two change points were negatively significant. The study highlights the efficacy of change point analysis in understanding the dynamics of covid-19 cases in India and across the world. It further helps to develop effective public health strategies. Elsevier B.V. 2022-06 2021-09-03 /pmc/articles/PMC8413104/ /pubmed/34493970 http://dx.doi.org/10.1016/j.spasta.2021.100538 Text en © 2021 Elsevier B.V. All rights reserved. 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 S.T., Pavan Kumar Lahiri, Biswajit Alvarado, Rafael Multiple change point estimation of trends in Covid-19 infections and deaths in India as compared with WHO regions |
title | Multiple change point estimation of trends in Covid-19 infections and deaths in India as compared with WHO regions |
title_full | Multiple change point estimation of trends in Covid-19 infections and deaths in India as compared with WHO regions |
title_fullStr | Multiple change point estimation of trends in Covid-19 infections and deaths in India as compared with WHO regions |
title_full_unstemmed | Multiple change point estimation of trends in Covid-19 infections and deaths in India as compared with WHO regions |
title_short | Multiple change point estimation of trends in Covid-19 infections and deaths in India as compared with WHO regions |
title_sort | multiple change point estimation of trends in covid-19 infections and deaths in india as compared with who regions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413104/ https://www.ncbi.nlm.nih.gov/pubmed/34493970 http://dx.doi.org/10.1016/j.spasta.2021.100538 |
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