Evidence map›Paper›PMID 33816091›Full record

ArticleResults in physics2021

Modeling the dynamics of novel coronavirus (COVID-19) via stochastic epidemic model.

Tahir Khan, Gul Zaman, Youssef El-Khatib

Abstract read
In one paragraph

Article in Results in physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  5. Numerical study of a nonlinear COVID-19 pandemic model by finite difference and meshless methods.Partial differential equations in applied mathematics : a spin-off of Applied Mathematics Letters · 2022
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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

3 authors.

Tahir KhanDepartment of Mathematics, University of Malakand, Chakdara, Dir (Lower), Khyber Pakhtunkhawa, Pakistan.
Gul ZamanDepartment of Mathematics, University of Malakand, Chakdara, Dir (Lower), Khyber Pakhtunkhawa, Pakistan.
Youssef El-KhatibDepartment of Mathematical Sciences, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this article we propose a stochastic model to discuss the dynamics of novel corona virus disease. We formulate the model to study the long run behavior in varying population environment. For this purposes we divided the total human population into three epidemiological compartments: the susceptible, covid-19 infected, recovered and recovered along with one class of reservoir. The existence and uniqueness of the newly formulated model will be studied to show the well-possedness of the model. Moreover, we investigate the extinction analysis as well as the persistence analysis to find the disease extinction and disease persistence conditions. At the end we perform simulation to justify the investigation of analytical work with the help of graphical representations.

Indexed as

COVID-19Existence and uniqueness analysisExtinction as well as persistenceSimulationStochastic model

Identifiers

PMID33816091
PMCPMC7999738

What OpenQuestion holds

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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.