Evidence map›Paper›PMID 41691157›Full record

ArticleBMC infectious diseases2026

The impact of treatment accessibility on HIV-TB co-infection: a comparative fractional-order modeling approach.

Agbata Benedict Celestine, Mehmet Gümüş, A K Awasthi, Homan Emadifar, Aseel Smerat, Bolarinwa Bolaji

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Article in BMC infectious diseases, 2026. 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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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Agbata Benedict CelestineDepartment of Mathematics and Statistics, Faculty of Science, Confluence University of Science and Technology, Osara-Okene, Nigeria. agbatacelestine92@gmail.com.
Mehmet GümüşDepartment of Mathematics,Faculty of Science,Zonguldak Bulent Ecevit University, Zonguldak, Türkiye.
A K AwasthiDepartment of Mathematics, School of Chemical Engineering and Physical Sciences, Lovely Professional University, Phagwara, Punjab, India.
Homan EmadifarDepartment of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, 602 105, India.
Aseel SmeratFaculty of Educational Sciences, Al-Ahliyya Amman University, Amman, 19328, Jordan.
Bolarinwa BolajiMathematical Sciences Department, Prince Abubakar Audu (Formerly, Kogi State) University, Anyigba, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

HIV-tuberculosis (TB) co-infection remains a major global health challenge, especially in regions with limited treatment accessibility. This study presents a fractional-order mathematical model that captured the transmission dynamics of HIV-TB co-infection among treated and untreated populations, incorporating disease progression through multiple compartments. The model is examined using three distinct fractional derivative operators, the Caputo derivative (power-law kernel), the Caputo–Fabrizio derivative (non-singular kernel), and the Atangana–Baleanu derivative (Mittag-Leffler kernel) to assess how memory effects influence infection dynamics. Treatment accessibility is represented as a factor modifying treatment and recovery rates, reflecting the proportion of infected individuals able to obtain timely medical care. Numerical simulations showed that dually infected populations experience significantly higher infection peaks compared to singly infected populations. This reflects a model-based result showing that, under the simulated parameter settings, the co-infection dynamics naturally produce higher peaks in dually infected groups than in singly infected populations. Variations in fractional orders (0.95, 0.85, and 0.75) significantly affect the temporal behavior and persistence of infection. Parameter values derived from current epidemiological data provide insight into the critical role of treatment accessibility in disease control. Numerical plots of the basic reproduction number () against key parameters illustrate that contact rates, treatment intensity, and accessibility levels strongly influence disease spread.The comparative operator analysis shows that expanding treatment accessibility consistently suppresses infection peaks across all fractional formulations, identifying it as the most effective and robust policy lever for controlling HIV–TB co-infection in resource-limited settings.Clinical trial numberNot applicable.

Indexed as

CoinfectionHealth Services AccessibilityHIV InfectionsTuberculosisComputer SimulationHumansModels, TheoreticalAtangana–baleanu derivativeCaputo derivativeCaputo–fabrizio derivativeHIV-TB co-infectionNumerical simulationPredictor-corrector methodTreatment accessibility

Identifiers

PMID41691157
PMCPMC12922354

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LicenceCC BY-NC-ND
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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.