Related Experiment Video
Updated: Jan 3, 2026

Humanized NOD/SCID/IL2rγnull (hu-NSG) Mouse Model for HIV Replication and Latency Studies
Published on: January 7, 2019
Competitive numerical analysis for stochastic HIV/AIDS epidemic model in a two-sex population
Ali Raza1, Muhammad Rafiq2, Dumitru Baleanu3
1Stochastic Analysis and Optimization Research Group, Department of Mathematics, Air University, PAF Complex E-9, Islamabad, Pakistan. 160865@students.au.edu.pk.
Abstract:
This study is an attempt to explain a reliable numerical analysis of a stochastic HIV/AIDS model in a two-sex population considering counselling and antiretroviral therapy (ART). The authors are comparing the solutions of the stochastic and deterministic HIV/AIDS epidemic model. Here, an endeavour has been made to explain the stochastic HIV/AIDS epidemic model is comparatively more pragmatic in contrast with the deterministic HIV/AIDS epidemic model. The effect of threshold number * holds on the stochastic HIV/AIDS epidemic model. If * < 1 then condition helps us to control disease in a two-sex human population while * > 1 explains the persistence of disease in the two-sex human population. Lamentably, numerical methods such as Euler-Maruyama, stochastic Euler, and stochastic Runge-Kutta do not work for large time step sizes. The recommended structure preserving framework of the stochastic non-standard finite difference (SNSFD) scheme conserve all vital characteristics such as positivity, boundedness, and dynamical consistency defined by Mickens. The effectiveness of counselling and ART may control HIV/AIDS in a two-sex population.
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Comparing the Survival Analysis of Two or More Groups
Population Growth
Mechanistic Models: Compartment Models in Individual and Population Analysis
Assumptions of Survival Analysis

