Evidence map›Paper›PMID 39774616›Full record

ArticleScientific reports2025

The role of a vaccine booster for a fractional order model of the dynamic of COVID-19: a case study in Thailand.

Puntipa Pongsumpun, Puntani Pongsumpun, I-Ming Tang, Jiraporn Lamwong

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Puntipa PongsumpunDepartment of Mathematics, School of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand.
Puntani PongsumpunDepartment of Mathematics, School of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand. puntani.po@kmitl.ac.th.
I-Ming TangDepartment of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand.
Jiraporn LamwongDepartment of Applied Basic Subjects, Thatphanom College, Nakhon Phanom University, Nakhon Phanom, 48000, Thailand. jiraporn99@npu.ac.th.

Funding

King Mongkut's Institute of Technology Ladkrabang KREF146504
6 · The paper itself

Abstract

This article addresses the critical need for understanding the dynamics of COVID-19 transmission and the role of booster vaccinations in managing the pandemic. Despite widespread vaccination efforts, the emergence of new variants and the waning of immunity over time necessitate more effective strategies. A fractional-order mathematical model using Caputo-Fabrizio derivatives was developed to analyze the impact of booster doses, symptomatic and asymptomatic infections, and quarantine measures. The model incorporates real epidemic data from Thailand and includes a sensitivity analysis of parameters influencing disease spread. Numerical results indicate that booster vaccinations significantly reduce transmission rates, and the model's predictions align well with the observed data. The basic reproduction number was determined to evaluate disease control, showing that a sustained vaccination campaign, including booster doses, is essential to maintaining immunity and controlling future outbreaks. The findings underscore the importance of ongoing vaccination efforts and provide a robust framework for policymakers to design effective strategies for pandemic control.

Indexed as

COVID-19COVID-19 VaccinesImmunization, SecondarySARS-CoV-2Basic Reproduction NumberHumansModels, TheoreticalPandemicsThailandVaccinationCOVID-19 VaccinesCaputo-Fabrizio derivativesCOVID-19Existence and uniquenessGlobal stabilityModel fittingVaccination

Identifiers

PMID39774616
PMCPMC11707013

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.