Fuzzy-fractional modeling of cholera disease using real outbreak data of angola in caputo-TFN framework

基于Caputo-TFN框架,利用安哥拉真实疫情数据对霍乱疾病进行模糊分数阶建模

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Abstract

Cholera is a waterborne disease that is mostly spread by taking tarnished food and water. This disease is brought on by bacteria Vibrio cholerae and causes infection in humans. The current manuscript proposes a fuzzy-fractional SEIHRD modeling framework for cholera disease outbreak in Angola using epidemiological data taken from World Health Organization. The Caputo fractional derivatives are used to capture the memory effects, while involved parameters are fuzzified using triangular fuzzy numbers for incorporating uncertainties involved in real-world data. The stability of the proposed model is examined to look at the circumstances in persistence and eradication of disease. For finding important factors influencing the dynamics of cholera transmission, sensitivity analysis is also carried out in this study. The effect of fractional and fuzzy parameters on the proposed model is analyzed via contour diagrams. The hybrid of fractional and fuzzy calculus yields a more realistic depiction of cholera dynamics, as depicted in numerical simulations. The analysis provides valuable results for planning public health initiatives for predicting and controlling cholera outbreaks.

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