|
|
 |
| |
|
|
|
Advanced Hantavirus Risk Assessment via an Integrated Fractional Neutrosophic Decision-Making Framework |
|
|
|
PP: 1717-1731 |
|
|
doi:10.18576/amis/200616
|
|
|
|
Author(s) |
|
|
|
Elsayed Badr,
Shokry Ibrahim Nada,
Saeed Ali,
Aya Rabie,
|
|
|
|
Abstract |
|
|
| Hantavirus infection represents a significant public health challenge because of its rapid transmission dynamics and the uncertainty inherent in epidemiological data. To overcome these challenges, this research develops a novel fractional Neutrosophic framework that combines fractional calculus with Neutrosophic set theory to better capture memory effects, indeterminacy, and inconsistent epidemiological information. A fractional Neutrosophic SIR model based on the Caputo fractional derivative is developed, and its fundamental mathematical properties, including positivity, boundedness, and equilibrium behavior, are investigated. Numerical simulations are performed to examine the effects of fractional-order dynamics and Neutrosophic uncertainty on disease transmission and epidemic evolution. Based on the simulation outcomes, several epidemiological and environmental indicators, such as infection rate, mortality severity, transmission intensity, rodent population density, healthcare capacity, and climate transmission risk, are evaluated across different epidemic regions. These model-generated indicators are then incorporated into a Neutrosophic TOPSIS framework to assess epidemic risk and rank regions under uncertain conditions. The results demonstrate that the proposed methodology effectively identifies high-risk regions and provides a reliable computational tool for epidemic prediction, uncertainty modeling, and healthcare risk evaluation, thereby supporting public health authorities in improving epidemic surveillance and strategic epidemic management. |
|
|
|
|
|
|
|
