Evidence map›Paper›PMID 33897091›Full record

ReviewApplied mathematical modelling2021

Review of fractional epidemic models.

Yuli Chen, Fawang Liu, Qiang Yu, Tianzeng Li

Open access · greenAbstract readReview
In one paragraph

Review in Applied mathematical modelling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
8.3field-weighted citation impact, top 2% 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

23 citing papers in PubMed, 145 citations in OpenAlex.

  1. Article
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  5. Wild canids and felids differ in their reliance on reused travel routeways.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  20. A Class of Deterministic and Stochastic Fractional Epidemic Models with Vaccination.Computational and mathematical methods in medicine · 2022
    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

4 authors at 3 institutions in 2 countries.

Yuli ChenFuzhou University Zhicheng College, Fujian 350001, China.
Fawang LiuSchool of Mathematical Sciences, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001, Australia.
Qiang YuSchool of Mathematical Sciences, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001, Australia.
Tianzeng LiSchool of Mathematics and Statistics, Sichuan University of Science and Engineering, Zigong 643000, China.
Queensland University of Technology · AUFuzhou University · CNSichuan University of Science and Engineering · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global impact of corona virus (COVID-19) has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 influenza A(H1N1) pandemic. In this paper, we have focused on reviewing the results of epidemiological modelling especially the fractional epidemic model and summarized different types of fractional epidemic models including fractional Susceptible-Infective-Recovered (SIR), Susceptible-Exposed-Infective-Recovered (SEIR), Susceptible-Exposed-Infective-Asymptomatic-Recovered (SEIAR) models and so on. Furthermore, we propose a general fractional SEIAR model in the case of single-term and multi-term fractional differential equations. A feasible and reliable parameter estimation method based on modified hybrid Nelder-Mead simplex search and particle swarm optimisation is also presented to fit the real data using fractional SEIAR model. The effective methods to solve the fractional epidemic models we introduced construct a simple and effective analytical technique that can be easily extended and applied to other fractional models, and can help guide the concerned bodies in preventing or controlling, even predicting the infectious disease outbreaks.

Indexed as

26A3337M0537N3097M60Epidemic modelsFractional order differential equationsHybrid simplex search and particle swarm optimisationImplicit numerical methodMulti-term epidemic modelsParameter estimation

Identifiers

PMID33897091
PMCPMC8056944
OpenAlexW3154982291

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.