Evidence map›Paper›PMID 40290618›Full record

ArticleBiomedical engineering and computational biology2025

Is it Curbing-spread of SARS-CoV-2 Variants by Considering Non-linear Predictive Control?

Mohadeseh Najafi, Hamidreza Mortazavy Beni, Ashkan Heydarian, Samaneh Sadat Sajjadi, Ahmad Hajipour

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical engineering and computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mohadeseh NajafiDepartment of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar, Iran.
Hamidreza Mortazavy BeniDepartment of Biomedical Engineering, Arsanjan Branch, Islamic Azad University, Arsanjan, Iran.ORCID https://orcid.org/0000-0002-6960-3251
Ashkan HeydarianDepartment of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.ORCID https://orcid.org/0000-0002-1283-6257
Samaneh Sadat SajjadiDepartment of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar, Iran.
Ahmad HajipourDepartment of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although SARS-COV-2 started in 2019, its losses are still significant, and it takes victims. In the present study, the epidemic patterns of SARS-COV-2 disease have been investigated from the point of view of mathematical modeling. Also, the effect of quarantine has been considered. This mathematical model is designed in the form of fractional calculations along with a model predictive control (MPC) to monitor this model. The fractional-order model has the memory and hereditary properties of the system, which can provide more adjustable parameters to the designer. Because the MPC can predict future outputs, it can overcome the conditions and events that occur in the future. The results of the simulations show that the proposed nonlinear model predictive controller (NMPC) of fractional-order has a lower mean squared error in susceptible people compared to the optimal control of fractional-order (~3.6e-04 vs. 47.4). This proposed NMPC of fractional-order can be used for other models of epidemics.

Indexed as

a nonlinear model predictive controlfractional-order calculationsMathematical modelSARS-COV-2

Identifiers

PMID40290618
PMCPMC12033554

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.