Optimal control dynamics of Gonorrhea in a structured population
Joshua Kiddy K. Asamoah,
Beilawu Safianu,
Emmanuel Afrifa,
Benjamin Obeng,
Baba Seidu,
Fredrick Asenso Wireko,
Gui-Quan Sun
Affiliations
Joshua Kiddy K. Asamoah
School of Mathematics, North University of China, Taiyuan, Shanxi 030051, China; Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Beilawu Safianu
Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Emmanuel Afrifa
Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Benjamin Obeng
Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Baba Seidu
Department of Mathematics, School of Mathematical Sciences, C. K. Tedam University of Technology and Applied Sciences, Navrongo, Ghana
Fredrick Asenso Wireko
Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Gui-Quan Sun
School of Mathematics, North University of China, Taiyuan, Shanxi 030051, China; Corresponding author.
Gonorrhea is a serious global health problem due to its high incidence, with approximately 82.4 million new cases in 2020. To evaluate the consequences of targeted dynamic control of gonorrhea infection transmission, a model for gonorrhea with optimal control analysis is proposed for a structured population. The study looked at the model's positively invariant and bounded regions. The gonorrhea secondary infection expression, R0 for the structured population is computed. The maximum principle of Pontryagin is utilised to construct the optimal system for the formulated mathematical model. To reduce the continuous propagation of gonorrhea, we incorporated education, condoms usage, vaccinations, and treatment as control strategies. The numerical simulations show that the number of infections decreases when the controls are implemented. The effectiveness of the controls is shown using the efficacy plots.
