Mpox is an infectious disease that is spread through close contact with contagious individuals or infected animals. Most people recover fully, but in some cases it can lead to serious illness or death. This study presents a data-driven dynamic model of Mpox virus transmission that incorporates the environment, demographic factors, and optimal control. Using the next-generation matrix approach, a basic reproduction number ( \(R_{0}\) ) of 0.722411 was calculated, suggesting that the Mpox disease will die out in the human population with time in Africa. The model equations were solved numerically using fourth- and fifth-order Runge–Kutta methods, with the forward-backward sweep technique applied to the optimal control problem. The model was calibrated to the historical Mpox data for Africa from May 2022 to August 2024 using the lsqcurvefit algorithm in the MATLAB software. The fitting algorithm yielded a mean absolute error (MAE) of 0.0044%, demonstrating a close alignment between the simulated and observed data. The optimized parameter values were used to project future Mpox dynamics. The key findings indicate that simultaneously decreasing the transmission rate by 25% and increasing the recovery rate by 10% would lead to a 31.75% reduction in the number of Mpox cases in Africa. In addition, the number of cumulative confirmed cases of Mpox in Africa is projected to reach approximately 83,427 by August 2025. However, with strict implementation of mass vaccination programs and public awareness campaigns, this number is projected to decrease by approximately 63.85%. Africa needs approximately 311,375,000 vaccine doses to effectively eradicate the Mpox virus by August 2025. The Ministry of Health should prioritize investing in mass vaccination programs to achieve optimal public health outcomes and economic benefits, aligning with Africa’s Vision 2063.
