Cargando…
Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India
OBJECTIVES: We study the effect of the coronavirus disease 2019 (COVID-19) in India and model the epidemic to guide those involved in formulating policy and building health-care capacity. METHODS: This effect is studied using the Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model. We...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7642509/ https://www.ncbi.nlm.nih.gov/pubmed/32900400 http://dx.doi.org/10.1017/dmp.2020.321 |
_version_ | 1783606101650964480 |
---|---|
author | Shah, Parth Vipul |
author_facet | Shah, Parth Vipul |
author_sort | Shah, Parth Vipul |
collection | PubMed |
description | OBJECTIVES: We study the effect of the coronavirus disease 2019 (COVID-19) in India and model the epidemic to guide those involved in formulating policy and building health-care capacity. METHODS: This effect is studied using the Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model. We estimate the infection rate using a least square method with Poisson noise and calculate the reproduction number. RESULTS: The infection rate is estimated to be 0.270 and the reproduction number to be 2.70. The approximate peak of the epidemic will be August 9, 2020. A 25% drop in infection rate will delay the peak by 11 d for a 1-mo intervention period. The total infected individuals in India will be 9% of the total population. CONCLUSIONS: The predictions are sensitive to changes in the behavior of people and their practice of social distancing. |
format | Online Article Text |
id | pubmed-7642509 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-76425092020-11-05 Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India Shah, Parth Vipul Disaster Med Public Health Prep Brief Report OBJECTIVES: We study the effect of the coronavirus disease 2019 (COVID-19) in India and model the epidemic to guide those involved in formulating policy and building health-care capacity. METHODS: This effect is studied using the Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model. We estimate the infection rate using a least square method with Poisson noise and calculate the reproduction number. RESULTS: The infection rate is estimated to be 0.270 and the reproduction number to be 2.70. The approximate peak of the epidemic will be August 9, 2020. A 25% drop in infection rate will delay the peak by 11 d for a 1-mo intervention period. The total infected individuals in India will be 9% of the total population. CONCLUSIONS: The predictions are sensitive to changes in the behavior of people and their practice of social distancing. Cambridge University Press 2020-09-09 /pmc/articles/PMC7642509/ /pubmed/32900400 http://dx.doi.org/10.1017/dmp.2020.321 Text en © Society for Disaster Medicine and Public Health, Inc. 2020 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Brief Report Shah, Parth Vipul Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India |
title | Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India |
title_full | Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India |
title_fullStr | Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India |
title_full_unstemmed | Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India |
title_short | Prediction of the Peak, Effect of Intervention, and Total Infected by COVID-19 in India |
title_sort | prediction of the peak, effect of intervention, and total infected by covid-19 in india |
topic | Brief Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7642509/ https://www.ncbi.nlm.nih.gov/pubmed/32900400 http://dx.doi.org/10.1017/dmp.2020.321 |
work_keys_str_mv | AT shahparthvipul predictionofthepeakeffectofinterventionandtotalinfectedbycovid19inindia |