Evidence map›Paper›PMID 41258492›Full record

ArticleScientific reports2025

On the dynamics of a COVID-19 model with vaccination and social processes.

M Juga, F Nyabadza

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

2 authors.

M JugaDepartment of Mathematics and Applied Mathematics, University of Johannesburg, Johannesburg, South Africa.
F NyabadzaDepartment of Mathematics and Applied Mathematics, University of Johannesburg, Johannesburg, South Africa. fnyabadza@uj.ac.za.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Following several nations' removal of COVID-19 restrictions, vaccination became the main COVID-19 control measure. Most countries engaged in massive vaccination to curb the disease's spread. Therefore, it is imperative that policymakers understand COVID-19 dynamics and prospective changes amid variances in COVID-19 vaccine coverage, especially in most African countries where vaccine uptake is generally lower than in high-income countries. This study presents a compartmental model for COVID-19, which incorporates dynamic social processes and vaccination. It is assumed that information about the infectious population invokes fear, which in turn influences social distancing and vaccination. Qualitative analysis of the model is carried out by determining its basic reproduction number, steady states, and global sensitivity of some of the parameters relative to the reproduction number. The model is calibrated using COVID-19 data for South Africa for the third and fourth waves. Numerical simulations are used to investigate the effects of vaccination and control measures. Based on the fitted data and simulations, we observed that a disease-free equilibrium state can easily be reached, and deaths can be averted if massive vaccination with a high-efficacy vaccine in combination with non-pharmaceutical interventions is used.

Indexed as

COVID-19COVID-19 VaccinesVaccinationBasic Reproduction NumberHumansModels, TheoreticalSARS-CoV-2South AfricaCOVID-19 VaccinesCorona Virus 2019FearReproduction numberSimulationsSocial distanceVaccination

Identifiers

PMID41258492
PMCPMC12630779

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.