SEIRD model to study the asymptomatic growth during COVID-19 pandemic in India.
Asymptomatic
COVID-19
Computational
SARS
SEIRD
Journal
Indian journal of physics and proceedings of the Indian Association for the Cultivation of Science (2004)
ISSN: 0973-1458
Titre abrégé: Indian J Phys Proc Indian Assoc Cultiv Sci (2004)
Pays: India
ID NLM: 101609844
Informations de publication
Date de publication:
2021
2021
Historique:
received:
05
06
2020
accepted:
16
09
2020
pubmed:
1
12
2020
medline:
1
12
2020
entrez:
30
11
2020
Statut:
ppublish
Résumé
According to the current perception, symptomatic, presymptomatic and asymptomatic infectious persons can infect the healthy population susceptible to the SARS-CoV-2. More importantly, various reports indicate that the number of asymptomatic cases can be several-fold higher than the reported symptomatic cases. In this article, we take the reported cases in India and various states within the country till September 1, as the specimen to understand the progression of the COVID-19. Employing a modified SEIRD model, we predict the spread of COVID-19 by the symptomatic as well as asymptomatic infectious population. Considering reported infection primarily due to symptomatic, we compare the model predicted results with the available data to estimate the dynamics of the asymptomatically infected population. Our data indicate that in the absence of the asymptomatic infectious population, the number of symptomatic cases would have been much less. Therefore, the current progress of the symptomatic infection can be reduced by quarantining the asymptomatically infectious population via extensive or random testing. This study is motivated strictly toward academic pursuit; this theoretical investigation is not meant for influencing policy decisions or public health practices.
Identifiants
pubmed: 33250600
doi: 10.1007/s12648-020-01928-8
pii: 1928
pmc: PMC7678779
doi:
Types de publication
Journal Article
Langues
eng
Pagination
2575-2587Informations de copyright
© Indian Association for the Cultivation of Science 2020.
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