Evidence map›Paper›PMID 34658543›Full record

ArticleChaos, solitons, and fractals2021

A fractional-order model for COVID-19 and tuberculosis co-infection using Atangana-Baleanu derivative.

A Omame, M Abbas, C P Onyenegecha

Open access · greenAbstract read
In one paragraph

Article in Chaos, solitons, and fractals, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
6.3field-weighted citation impact, top 3% of its field
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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 85 citations in OpenAlex.

  1. Pooled it
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  5. Article
  6. Article
  7. A mathematical model for the co-dynamics of COVID-19 and tuberculosis.Mathematics and computers in simulation · 2023
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  12. Fractal-fractional age-structure study of omicron SARS-CoV-2 variant transmission dynamics.Partial differential equations in applied mathematics : a spin-off of Applied Mathematics Letters · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. On fractal-fractional Covid-19 mathematical model.Chaos, solitons, and fractals · 2022
    Article
  17. Article
  18. 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

3 authors at 2 institutions in 3 countries.

A OmameDepartment of Mathematics, Federal University of Technology, Owerri, Nigeria.
M AbbasDepartment of Mathematics, Government College University Katchery Road, Lahore 54000, Pakistan and Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 40402, Taiwan.
C P OnyenegechaDepartment of Physics, Federal University of Technology, Owerri, Nigeria.
Federal University of Technology Owerri · NGChina Medical University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper considers and analyzes a fractional order model for COVID-19 and tuberculosis co-infection, using the Atangana-Baleanu derivative. The existence and uniqueness of the model solutions are established by applying the fixed point theorem. It is shown that the model is locally asymptotically stable when the reproduction number is less than one. The global stability analysis of the disease free equilibrium points is also carried out. The model was simulated using data relevant to both diseases in New Delhi, India. Fitting the model to the cumulative confirmed COVID-19 cases for New Delhi from March 1, 2021 to June 26, 2021, COVID-19 and TB contact rates and some other important parameters of the model are estimated. The numerical method used combines the two-step Lagrange polynomial and the fundamental theorem of fractional calculus and has been shown to be highly accurate and efficient, user-friendly and converges quickly to the exact solution even with a large step of discretization. Simulations of the Fractional order model revealed that reducing the risk of COVID-19 infection by latently-infected TB individuals will not only bring down the burden of COVID-19, but will also reduce the co-infection of both diseases in the population. Also, the conditions for the co-existence or elimination of both diseases from the population are established.

Indexed as

COVID-19Fixed pointFractional derivativeModel-fittingTuberculosis

Identifiers

PMID34658543
PMCPMC8501266
OpenAlexW3207013555

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.