Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66706
Volume:
10 |
8 |
Aug 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
DEPARTMENT OF MATHEMATICS
JCD MEMORIAL COLLEGE, SIRSA
Chikungunya and dengue are both mosquito-borne viral diseases transmitted by Aedes species, yet they have typically been modelled in isolation using structurally different compartmental frameworks — a demographic SEIR model for Chikungunya and a logistic, carrying-capacity-augmented SEIR model for dengue. This paper places both diseases within a single comparative numerical study, solving each model with its disease-specific parameters via high-order Runge-Kutta integration (SciPy's adaptive RK45 solver) and directly comparing their outbreak trajectories, peak infection timing, and basic reproduction numbers. The comparison shows that the Chikungunya model produces a monotonically rising infected class over its short reporting horizon with no internal turning point, consistent with an unstable, still-escalating outbreak, whereas the logistic-growth dengue model exhibits an early infection peak followed by decline as the susceptible pool approaches carrying capacity. These differences are attributed principally to the presence of density-dependent (logistic) susceptible growth in the dengue model, which is absent from the Chikungunya formulation, and we discuss the implications for model selection in short- versus long-horizon vector-borne outbreak analysis.
KEYWORDS
This paper presented a direct numerical comparison of Chikungunya and dengue outbreak dynamics using each disease's published model structure, solved with a common, reproducible Runge-Kutta method. The results show materially different outbreak shapes — a still-escalating outbreak for Chikungunya versus a peak-and-decline pattern for dengue — driven substantially by the presence or absence of logistic susceptible-class growth in the two model formulations, rather than solely by disease-specific transmission or recovery parameters. This underscores the importance of structural model choice, not just parameter estimation, in cross-disease comparative epidemiology, and points toward unified-structure comparative modelling as a valuable direction for future work aimed at disentangling genuine epidemiological differences between co-circulating vector-borne diseases from artefacts of inconsistent modelling practice across the literature.
Kermack, W. O., & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society A, 115(772), 700-721. Ross, R. (1911). The Prevention of Malaria (2nd ed.). John Murray. Verhulst, P. F. (1838). Notice sur la loi que la population suit dans son accroissement. Correspondance Mathématique et Physique, 10, 113-121. Moulay, D., Aziz-Alaoui, M. A., & Cadivel, M. (2011). The chikungunya disease: modeling, vector and transmission global dynamics. Mathematical Biosciences, 229(1), 50-63. Isea, R., & Lonngren, K. E. (2016). A mathematical model for the co-infection of Dengue, Chikungunya and Zika. Applied Mathematics, 7, 1-8. Pongsumpun, P. (2008). Mathematical model of dengue disease with the incubation period of virus. World Academy of Science, Engineering and Technology, 44, 328-332. Phaijoo, G. R., & Gurung, D. B. (2017). Mathematical model of dengue disease transmission dynamics with control measures. Journal of Advances in Mathematics and Computer Science, 23(3), 1-12. Virtanen, P., et al. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17, 261-272.
Publication Date
8/12/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
1
Total views since publication
PDF Downloads
4
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...