| dc.description.abstract | The incorporation of fuzzy analysis in the mathematical modeling of disease outbreaks has
brought a paradigm shift in epidemiological research, offering a sophisticated approach to
understanding and addressing the complexities inherent in disease dynamics. Unlike traditional
mathematical models, which often rely on deterministic assumptions and precise parameter
values, fuzzy analysis provides a flexible framework capable of accommodating uncertainty
and imprecision within epidemiological systems. This paper presents a novel SVEIR-SEI com-
partmental model for dengue disease where five key parameters such as transmission rate,
mortality rate, recovery rate, biting rate, and vaccination rate are treated as fuzzy numbers.
Among these, transmission rate, mortality rate, and recovery rate are defined as a function of
virus load whereas biting rate and vaccinations rate are defined as a function of number of bed
net users and media awareness regarding vaccination, respectively. Crisp reproduction number
is determined using next generation matrix method and hence fuzzy reproduction number
is derived as a triangular fuzzy number (TFN). Numerical results show that biting rate and
vaccination rate are the two most sensitive parameters to crisp reproduction number. We also
examine the impact of using bed nets and media awareness regarding vaccination on the model
system under fuzzy environment. It is found that using bed nets is a more effective strategy for
dengue control than media coverage regarding vaccination. | en_US |
