Evidence map›Paper›PMID 33250600›Full record

ArticleIndian journal of physics and proceedings of the Indian Association for the Cultivation of Science (2004)2021

SEIRD model to study the asymptomatic growth during COVID-19 pandemic in India.

Saptarshi Chatterjee, Apurba Sarkar, Mintu Karmakar, Swarnajit Chatterjee, Raja Paul

Abstract read
In one paragraph

Article in Indian journal of physics and proceedings of the Indian Association for the Cultivation of Science (2004), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. A mathematical model of COVID-19 transmission.Materials today. Proceedings · 2022
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Saptarshi ChatterjeeIndian Association for the Cultivation of Science, Kolkata, 700032 India.
Apurba SarkarIndian Association for the Cultivation of Science, Kolkata, 700032 India.
Mintu KarmakarIndian Association for the Cultivation of Science, Kolkata, 700032 India.
Swarnajit ChatterjeeIndian Association for the Cultivation of Science, Kolkata, 700032 India.
Raja PaulIndian Association for the Cultivation of Science, Kolkata, 700032 India.ORCID 0000-0001-7045-8584

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

AsymptomaticComputationalCOVID-19SARSSEIRD

Identifiers

PMID33250600
PMCPMC7678779

What OpenQuestion holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.