Advanced fractional-order mathematical modeling of scabies integrating transmission dynamics, demographics, mite ecology, and real-world data
Results in Control and Optimization, cilt.24, 2026 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 24
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.rico.2026.100783
- Dergi Adı: Results in Control and Optimization
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
- Anahtar Kelimeler: Demographic factors, Ecology, Mathematical modeling, Public health, Scabies dynamics
- Karadeniz Teknik Üniversitesi Adresli: Hayır
Özet
Background: Scabies continues to affect around 300 million individuals each year and persists as a major neglected tropical disease. Problem statement: Current mathematical models generally fail to incorporate gender- and age-specific population structure (particularly the vulnerable 15–24 age group), comprehensive mite population dynamics, real clinical datasets, and the memory-dependent behavior captured by fractional calculus. Methods: This study proposes a novel ten-compartment Caputo fractional-order model that distinguishes four susceptible subgroups according to gender and age (15–24 years versus all other ages), while also tracking exposed, symptomatic, asymptomatic, and recovered individuals together with an explicit mite population compartment. The model is parameterized using real hospital records collected between 2017 and 2023. Model properties are examined analytically, and numerical simulations are performed. The chosen age grouping is motivated by hospital data revealing markedly higher incidence rates among 15–24-year-olds, attributable to increased social and sexual contact as well as shared living environments. Results and findings: Sensitivity analysis identifies the transmission rate as the most influential parameter. The susceptible population in the 15–24 age bracket decreases at a markedly faster rate than other groups. Raising the fractional order accelerates early epidemic growth yet enhances the apparent effectiveness of control measures and produces stronger reduction in the mite population. The fractional formulation accounts for memory effects and delivers improved long-term forecasting performance compared with conventional integer-order models. Conclusion: The proposed framework identifies clear intervention priorities focused on young adults and mite control, thereby supporting global efforts to meet the WHO 2030 targets for scabies elimination.