Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Dec 28;14(1):30706.
doi: 10.1038/s41598-024-79475-z.

Modeling and analysis of dengue transmission in fuzzy-fractional framework: a hybrid residual power series approach

Mubashir Qayyum  1 , Qursam Fatima  1 , Ali Akgül  2   3   4 , Murad Khan Hassani  5
Affiliations

Modeling and analysis of dengue transmission in fuzzy-fractional framework: a hybrid residual power series approach

Mubashir Qayyum et al. Sci Rep. .

Abstract

The current manuscript presents a mathematical model of dengue fever transmission with an asymptomatic compartment to capture infection dynamics in the presence of uncertainty. The model is fuzzified using triangular fuzzy numbers (TFNs) approach. The obtained fuzzy-fractional dengue model is then solved and analyzed through fuzzy extension of modified residual power series algorithm, which utilizes residual power series along with Laplace transform. Numerical analysis has also been performed in this study and obtained results are shown as solutions and residual errors for each compartment to ensure the validity. Graphical analysis depict the model's behavior under varying parameters, illustrating contrasting trends for different values of ν and examining the impacts of transmission and recovery rates on dengue model in uncertain environment. The current findings highlighted the effectiveness of proposed uncertainty in epidemic system dynamics, offering new insights with potential applications in other areas of engineering, science and medicine.

Keywords: Caputo fractional derivative; Fuzzy-fractional model; Residual power series; Triangular fuzzy numbers.

PubMed Disclaimer

Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Effect of biting rate per person per mosquito on different classes of dengue model.
Fig. 2
Fig. 2
Effect of incubation rates of mosquitoes and humans on different classes of dengue model.
Fig. 3
Fig. 3
Fuzzy lower and upper bound solutions of fuzzy-fractional dengue model at different fractional points.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Ajlan, Balgees A. et al. Assessment of the new world health organization’s dengue classification for predicting severity of illness and level of healthcare required. PLoS Negl. Trop. Dis.13(8), e0007144 (2019). - PMC - PubMed
    1. Bhatt, S. et al. The global distribution and burden of dengue. Nature496(7446), 504–507 (2013). - PMC - PubMed
    1. Rodriguez-Roche, Rosmari & Gould, Ernest A. Understanding the dengue viruses and progress towards their control. Biomed. Res. Int.1–20, 2013 (2013). - PMC - PubMed
    1. Atangana, Abdon & Khan, Muhammad Altaf. Analysis of fractional global differential equations with power law. AIMS Math.8(10), 24699–24725 (2023).
    1. Khan, Muhammad Altaf & Atangana, Abdon. Numerical Methods for Fractal-Fractional Differential Equations and Engineering: Simulations and Modeling (CRC Press, 2023).