Modeling of Eye Infection Transmitting by Conjunctivitis Adenovirus: Deterministic and Stochastic Approach

Abstract

This study develops a mathematical model to investigate the early diagnosis and treatment of conjunctivitis caused by adenovirus, incorporating both deterministic and stochastic approaches to capture disease dynamics. The model’s fundamental properties, including boundedness and uniqueness, are analyzed to ensure reliability, and equilibrium points are established for the deterministic framework. The basic reproduction number is derived and subjected to sensitivity analysis to evaluate how key parameters influence the spread of infection. Numerical simulations, conducted using a nonstandard finite difference (NSFD) scheme for the deterministic model and stochastic methods for the probabilistic model, reveal that individuals with strong immune systems can recover without medical intervention, highlighting the critical role of immune strength in controlling disease transmission. These findings contribute to a deeper understanding of conjunctivitis dynamics and provide valuable insights for designing effective control strategies based on early diagnosis and treatment.