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SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions
Background: After SARS-CoV-2 set foot in India, the Government took a number of steps to limit the spread of the virus in the country. This included restricted testing, isolation, contact tracing and quarantine, and enforcement of a nation-wide lockdown starting 25 March 2020. The objectives of this...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262570/ https://www.ncbi.nlm.nih.gov/pubmed/32528664 http://dx.doi.org/10.12688/f1000research.23496.2 |
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author | Mazumder, Archisman Arora, Mehak Bharadiya, Vishwesh Berry, Parul Agarwal, Mudit Behera, Priyamadhaba Shewade, Hemant Deepak Lohiya, Ayush Gupta, Mohak Rao, Aditi Parameswaran, Giridara Gopal |
author_facet | Mazumder, Archisman Arora, Mehak Bharadiya, Vishwesh Berry, Parul Agarwal, Mudit Behera, Priyamadhaba Shewade, Hemant Deepak Lohiya, Ayush Gupta, Mohak Rao, Aditi Parameswaran, Giridara Gopal |
author_sort | Mazumder, Archisman |
collection | PubMed |
description | Background: After SARS-CoV-2 set foot in India, the Government took a number of steps to limit the spread of the virus in the country. This included restricted testing, isolation, contact tracing and quarantine, and enforcement of a nation-wide lockdown starting 25 March 2020. The objectives of this study were to i) describe the age, gender distribution, and mortality among COVID-19 patients identified till 14 April 2020 and predict the range of contact rate; and ii) predict the number of COVID-19 infections after 40 days of lockdown. Methods: We used a cross-sectional descriptive design for the first objective and a susceptible-infected-removed model for in silico predictions. We collected data from government-controlled and crowdsourced websites. Results: Studying age and gender parameters of 1161 Indian COVID-19 patients, the median age was 38 years (IQR, 27-52) with 20-39 year-old males being the most affected group. The number of affected patients were 854 (73.6%) men and 307 (26.4%) women. If the current contact rate continues (0.25-27), India may have 110460 to 220575 infected persons at the end of 40 days lockdown. Conclusion: The disease is majorly affecting a younger age group in India. Interventions have been helpful in preventing the worst-case scenario in India but will be unable to prevent the spike in the number of cases. |
format | Online Article Text |
id | pubmed-7262570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-72625702020-06-10 SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions Mazumder, Archisman Arora, Mehak Bharadiya, Vishwesh Berry, Parul Agarwal, Mudit Behera, Priyamadhaba Shewade, Hemant Deepak Lohiya, Ayush Gupta, Mohak Rao, Aditi Parameswaran, Giridara Gopal F1000Res Research Article Background: After SARS-CoV-2 set foot in India, the Government took a number of steps to limit the spread of the virus in the country. This included restricted testing, isolation, contact tracing and quarantine, and enforcement of a nation-wide lockdown starting 25 March 2020. The objectives of this study were to i) describe the age, gender distribution, and mortality among COVID-19 patients identified till 14 April 2020 and predict the range of contact rate; and ii) predict the number of COVID-19 infections after 40 days of lockdown. Methods: We used a cross-sectional descriptive design for the first objective and a susceptible-infected-removed model for in silico predictions. We collected data from government-controlled and crowdsourced websites. Results: Studying age and gender parameters of 1161 Indian COVID-19 patients, the median age was 38 years (IQR, 27-52) with 20-39 year-old males being the most affected group. The number of affected patients were 854 (73.6%) men and 307 (26.4%) women. If the current contact rate continues (0.25-27), India may have 110460 to 220575 infected persons at the end of 40 days lockdown. Conclusion: The disease is majorly affecting a younger age group in India. Interventions have been helpful in preventing the worst-case scenario in India but will be unable to prevent the spike in the number of cases. F1000 Research Limited 2020-06-29 /pmc/articles/PMC7262570/ /pubmed/32528664 http://dx.doi.org/10.12688/f1000research.23496.2 Text en Copyright: © 2020 Mazumder A et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Mazumder, Archisman Arora, Mehak Bharadiya, Vishwesh Berry, Parul Agarwal, Mudit Behera, Priyamadhaba Shewade, Hemant Deepak Lohiya, Ayush Gupta, Mohak Rao, Aditi Parameswaran, Giridara Gopal SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions |
title | SARS-CoV-2 epidemic in India: epidemiological features and
in silico analysis of the effect of interventions |
title_full | SARS-CoV-2 epidemic in India: epidemiological features and
in silico analysis of the effect of interventions |
title_fullStr | SARS-CoV-2 epidemic in India: epidemiological features and
in silico analysis of the effect of interventions |
title_full_unstemmed | SARS-CoV-2 epidemic in India: epidemiological features and
in silico analysis of the effect of interventions |
title_short | SARS-CoV-2 epidemic in India: epidemiological features and
in silico analysis of the effect of interventions |
title_sort | sars-cov-2 epidemic in india: epidemiological features and
in silico analysis of the effect of interventions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7262570/ https://www.ncbi.nlm.nih.gov/pubmed/32528664 http://dx.doi.org/10.12688/f1000research.23496.2 |
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