Employing Fuzzy Logic to Analyze the Structure of Complex Biological and Epidemic Spreading Models

Abstract

Complex networks constitute a new field of scientific research that is derived from the observation and analysis of real-world networks, for example, biological, computer and social ones. An important subset of complex networks is the biological, which deals with the numerical examination of connections/associations among different nodes, namely interfaces. These interfaces are evolutionary and physiological, where network epidemic models or even neural networks can be considered as representative examples. The investigation of the corresponding biological networks along with the study of human diseases has resulted in an examination of networks regarding medical supplies. This examination aims at a more profound understanding of concrete networks. Fuzzy logic is considered one of the most powerful mathematical tools for dealing with imprecision, uncertainties and partial truth. It was developed to consider partial truth values, between completely true and completely false, and aims to provide robust and low-cost solutions to real-world problems. In this manuscript, we introduce a fuzzy implementation of epidemic models regarding the Human Immunodeficiency Virus (HIV) spreading in a sample of needle drug individuals. Various fuzzy scenarios for a different number of users and different number of HIV test samples per year are analyzed in order for the samples used in the experiments to vary from case to case. To the best of our knowledge, analyzing HIV spreading with fuzzy-based simulation scenarios is a research topic that has not been particularly investigated in the literature. The simulation results of the considered scenarios demonstrate that the existence of fuzziness plays an important role in the model setup process as well as in analyzing the effects of the disease spread.

Computational study of a co-infection model of HIV/AIDS and hepatitis C virus models

“…In this section, we will investigate a novel approach, the NSFD technique, which relies on Micken's theory for the solutions of the dynamic systems (24,25) and (35)(36)(37)(38).…”

“…Given the inherent uncertainty of HIV/AIDS, the transmission rate is modeled as a fuzzy set based on viral load 24 . A fuzzy-oriented approach is introduced to epidemiological models concerning the prevalence of HIV within a cohort of individuals engaged in injectable drug use 25 . A comprehensive analysis encompassed various fuzzy scenarios, exploring diverse user counts and different quantities of HIV test samples conducted annually.…”

A reliable numerical investigation of an SEIR model of measles disease dynamics with fuzzy criteria

“…A SIR model with imprecise biological factors was presented by Das and Pal 47 . Lefevre et al discussed applications of fuzzy epidemiological models related to the prevalence of HIV 48 . Dandapanet et al recently introduced a model by using fuzzy logic and solved by using Laplace-Adoman analysis method and differential transform method for an arbitrary order 49 .…”