Evidence map›Paper›PMID 35447461›Full record

ArticleComputers in biology and medicine2022

Mathematical modeling of COVID-19 pandemic in India using Caputo-Fabrizio fractional derivative.

Prashant Pandey, J F Gómez-Aguilar, Mohammed K A Kaabar, Zailan Siri, Abd Allah A Mousa

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Article in Computers in biology and medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
7.4field-weighted citation impact, top 1% 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

6 citing papers in PubMed, 56 citations in OpenAlex.

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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

5 authors at 3 institutions in 4 countries.

Prashant PandeyDepartment of Mathematics, Government M.G.M. P.G. College, Itarsi, 461111, India.
J F Gómez-AguilarCONACyT-Tecnológico Nacional de México/CENIDET, Interior Internado Palmira S/N, Col. Palmira, C.P. 62490, Cuernavaca Morelos, Mexico. Electronic address: jose.ga@cenidet.tecnm.mx.
Mohammed K A KaabarGofa Camp, Near Gofa Industrial College and German Adebabay, Nifas Silk-Lafto, 26649, Addis Ababa, Ethiopia; Institute of Mathematical Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, 50603, Malaysia. Electronic address: mohammed.kaabar@wsu.edu.
Zailan SiriInstitute of Mathematical Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, 50603, Malaysia.
Abd Allah A MousaDepartment of Mathematics and Statistics, College of Science, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia.
University of Malaya · MYTaif University · SATecnológico Nacional de México · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The range of effectiveness of the novel corona virus, known as COVID-19, has been continuously spread worldwide with the severity of associated disease and effective variation in the rate of contact. This paper investigates the COVID-19 virus dynamics among the human population with the prediction of the size of epidemic and spreading time. Corona virus disease was first diagnosed on January 30, 2020 in India. From January 30, 2020 to April 21, 2020, the number of patients was continuously increased. In this scientific work, our main objective is to estimate the effectiveness of various preventive tools adopted for COVID-19. The COVID-19 dynamics is formulated in which the parameters of interactions between people, contact tracing, and average latent time are included. Experimental data are collected from April 15, 2020 to April 21, 2020 in India to investigate this virus dynamics. The Genocchi collocation technique is applied to investigate the proposed fractional mathematical model numerically via Caputo-Fabrizio fractional derivative. The effect of presence of various COVID parameters e.g. quarantine time is also presented in the work. The accuracy and efficiency of the outputs of the present work are demonstrated through the pictorial presentation by comparing it to known statistical data. The real data for COVID-19 in India is compared with the numerical results obtained from the concerned COVID-19 model. From our results, to control the expansion of this virus, various prevention measures must be adapted such as self-quarantine, social distancing, and lockdown procedures.

Indexed as

COVID-19Communicable Disease ControlHumansIndiaModels, TheoreticalPandemicsSARS-CoV-2Caputo-fabrizio fractional derivativeCollocation techniqueCOVID-19Genocchi polynomialInfectious diseasesModel predictionPandemic slow down

Identifiers

PMID35447461
PMCPMC9009075
OpenAlexW4224020210

What OpenQuestion holds

Textmetadata
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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.