SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions [version 1; peer review: 2 approved]
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...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2020-04-01
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| Series: | F1000Research |
| Online Access: | https://f1000research.com/articles/9-315/v1 |
| _version_ | 1818342447456976896 |
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| author | Archisman Mazumder Mehak Arora Vishwesh Bharadiya Parul Berry Mudit Agarwal Priyamadhaba Behera Hemant Deepak Shewade Ayush Lohiya Mohak Gupta Aditi Rao Giridara Gopal Parameswaran |
| author_facet | Archisman Mazumder Mehak Arora Vishwesh Bharadiya Parul Berry Mudit Agarwal Priyamadhaba Behera Hemant Deepak Shewade Ayush Lohiya Mohak Gupta Aditi Rao Giridara Gopal Parameswaran |
| author_sort | Archisman Mazumder |
| collection | DOAJ |
| 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 active COVID-19 patients after 40 days of lockdown. Methods: We used a cross-sectional descriptive design for 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 number of cases. |
| first_indexed | 2024-12-13T16:14:50Z |
| format | Article |
| id | doaj.art-2c0406fe78114557958e04b6916bd7fa |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-12-13T16:14:50Z |
| publishDate | 2020-04-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-2c0406fe78114557958e04b6916bd7fa2022-12-21T23:38:51ZengF1000 Research LtdF1000Research2046-14022020-04-01910.12688/f1000research.23496.125930SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions [version 1; peer review: 2 approved]Archisman Mazumder0Mehak Arora1Vishwesh Bharadiya2Parul Berry3Mudit Agarwal4Priyamadhaba Behera5Hemant Deepak Shewade6Ayush Lohiya7Mohak Gupta8Aditi Rao9Giridara Gopal Parameswaran10All India Institute of Medical Sciences, New Delhi, Delhi, IndiaAll India Institute of Medical Sciences, New Delhi, Delhi, IndiaAll India Institute of Medical Sciences, New Delhi, Delhi, IndiaAll India Institute of Medical Sciences, New Delhi, Delhi, IndiaAll India Institute of Medical Sciences, New Delhi, Delhi, IndiaAll India Institute of Medical Sciences, Raebareli, Uttar Pradesh, IndiaOperational Research, The Union South-East Asia Office, New Delhi, Delhi, IndiaSuper Specialty Cancer Institute & Hospital, Lucknow, IndiaAll India Institute of Medical Sciences, New Delhi, Delhi, IndiaAll India Institute of Medical Sciences, New Delhi, Delhi, IndiaAll India Institute of Medical Sciences, New Delhi, Delhi, IndiaBackground: 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 active COVID-19 patients after 40 days of lockdown. Methods: We used a cross-sectional descriptive design for 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 number of cases.https://f1000research.com/articles/9-315/v1 |
| spellingShingle | Archisman Mazumder Mehak Arora Vishwesh Bharadiya Parul Berry Mudit Agarwal Priyamadhaba Behera Hemant Deepak Shewade Ayush Lohiya Mohak Gupta Aditi Rao Giridara Gopal Parameswaran SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions [version 1; peer review: 2 approved] F1000Research |
| title | SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions [version 1; peer review: 2 approved] |
| title_full | SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions [version 1; peer review: 2 approved] |
| title_fullStr | SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions [version 1; peer review: 2 approved] |
| title_full_unstemmed | SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions [version 1; peer review: 2 approved] |
| title_short | SARS-CoV-2 epidemic in India: epidemiological features and in silico analysis of the effect of interventions [version 1; peer review: 2 approved] |
| title_sort | sars cov 2 epidemic in india epidemiological features and in silico analysis of the effect of interventions version 1 peer review 2 approved |
| url | https://f1000research.com/articles/9-315/v1 |
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