OPTIMAL CONTROL ON MATHEMATICAL MODEL OF MPOX DISEASE SPREAD
Abstract
The Global emergency related to mpox infection outside endemic areas occurred in 2022. The United States is one of the areas that has been significantly impacted by the mpox virus. To reduce the number of infection cases, it is essential to control the spread of the disease. This can be achieved through optimal control. The intervention provided to combat the dynamic spread of mpox can be represented in the form of a mathematical model. This model comprises the animal population (SEI) and the human population (SEIR). Furthermore, the model that has been formed also divides humans into high-risk and low-risk populations. The classification is based on the risk of complications and death caused by infection. The model will be analyzed in order to ascertain its disease-free and endemic stability. The spread of mpox is then controlled by healthy living behaviors and antiviral administration to reduce the number of infection cases. To this end, numerical simulations were conducted to visualize the spread of mpox with and without the function of control variables so that optimal results were obtained. The results of the numerical simulation demonstrate that a reduction in infection cases by 64.62% can be achieved by implementing an average rate of healthy living behaviors of 93.15% and distributing an average rate of antivirus at 75.11%.
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