Muli, Charles NdambukiKimulu, Ancent Makau2024-07-092024-07-092024-05Muli, C. N., & Kimulu, A. M. OPTIMIZING VACCINATION STRATEGIES TO REDUCE CONJUNCTIVITIS TRANSMISSION: MATHEMATICAL MODELING INSIGHTS FROM KENYA.https://www.doi.org/10.56726/IRJMETS57623https://ir-library.ku.ac.ke/handle/123456789/28428ArticleConjunctivitis is a widespread condition with significant public health implications, but its potential impact on transmission patterns due to vaccination programs, particularly in Kenya, remains underexplored. The main aims of this study to investigate the role of vaccination in preventing conjunctivitis spread and related complications. A deterministic mathematical model was developed in an attempt to simulate conjunctivitis incidence, considering factors like population size, contact rates, and vaccination efficacy. The basic reproduction number (R₀) was calculated using the next-generation matrix method. Stability analysis of the disease-free equilibrium (DFE) showed stability will occur when R₀ < 1 and instability when R₀ > 1. Numerical computations using the MATLAB ode45 solver indicated that increased vaccination campaigns reduce the infected population. This implies that vaccination strengthens the immune response against the infection, lowering the risk of severe outcomes like vision loss. This study is vital for understanding the potential impact of effective vaccination programs on conjunctivitis transmission in Kenya, aiding policy-makers and public health practitioners in developing effective disease control measures.enConjunctivitisMathematical ModelingNext Generation MatrixTransmission DynamicsVaccination CampaignsArticle