Abdulsamad Engida Sado

HIV/AIDS remains a major global health problem that is strongly shaped by socioeconomic conditions and workforce productivity. This work develops and analy

HIV/AIDS deeply affects society, forcing people to leave their jobs and family responsibilities. This not only impacts their lives but also has a negative effect on the economy. HIV/AIDS affects development and growth by lowering productivity, income, and poverty levels. This study examines the impact of HIV/AIDS on Ethiopia’s workingclass population using mathematical and neural network-based modeling, aiming to develop an accurate predictive framework. A supervised DNN with sigmoid activation is trained on WHO data (2000-2023) to predict disease incidence and transmission. Numerical simulations show that utilizing feedforward DNN methods gives precise solutions for advanced epidemiological models. The model attained a prediction accuracy above 99% and revealed a gradual rise in HIV incidence among nonproductive individuals over two decades. Finally, the trend of HIV/AIDS infection in Ethiopia from 2024 to 2050 is forecasted. The full-blown AIDS and infected class population approaches zero. Based on our estimated parameters and numerical simulations, it is evident that the application of neural network methods marks a significant advancement in the field of epidemiological modeling.

Pneumonia has been a major airborne transmitted disease and continues to pose a major public health problem in both developed and developing countries of the world. In this study, we constructed and analyzed a non-linear deterministic mathematical model in case of Bule Hora town for assessing the community-level impacts of natural immunity, other protection measures and treatment on the transmission dynamics of pneumonia disease in a population of varying size. Our model exhibits two kinds of equilibrium points: pneumonia disease-free equilibrium point, and pneumonia endemic equilibrium point. Thus, for pneumonia infection, the necessity of the pneumonia reproduction number R 0 < 1, although essential, it might not be enough to completely eradicate the pneumonia infection from the considered community. Our examination of sensitivity analysis shows that the pneumonia infection transmission rate plays a crucial role to change the qualitative behavior of dynamics of pneumonia infection. By taking standard data from Bule hora teaching Hospital and published literature, our numerical computations show that the numerical value of pneumonia infection model reproduction number greater than one it implies that the disease spreads throughout the community. Finally, our numerical simulations show that natural immunity and treatment against pneumonia disease have effectively decreasing pneumonia expansion.