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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...

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Autor principal: Shah, Parth Vipul
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
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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.
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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
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