Iranian Journal of Numerical Analysis and Optimization

Iranian Journal of Numerical Analysis and Optimization

Mathematical modeling and control strategies for meningitis transmission

Document Type : Research Article

Authors
1 Laboratory of Advanced Research in Industrial and Logistic Engineering (LARILE), Applied Mathematics Team, Department of Mathematics and Computer Science, ENSEM, Hassan II University of Casablanca, Morocco.
2 Centre R´egional des M´etiers de l’´Education et de la Formation (CRMEF), 20340 Derb Ghalef, Casablanca, Morocco.
3 Laboratory of Analysis Modeling and Simulation, Department of Mathematics and Computer Science, Faculty of Sciences Ben M’sik, Hassan II University of Casablanca, Morocco.
10.22067/ijnao.2026.96797.1789
Abstract
Meningitis is one of the world’s most alarming infectious diseases, characterized by rapid progression, high fatality, and severe long-term complications. Despite advances in vaccination and surveillance, recurrent epidemics—especially across Africa’s “meningitis belt”—continue to threaten millions. This study introduces a novel compartmental model, SEAIV HRQ, integrating both medical and behavioral aspects of meningitis dynamics. The model divides the population into eight classes, incorporating vaccination and voluntary quarantine to reflect realistic public health conditions. Three time-dependent controls are applied to reduce transmission from asymptomatic and symptomatic individuals and to enhance awareness and treatment adherence. Using Pontryagin’s Maximum Principle, we determine optimal strategies that minimize infection prevalence, hospitalization, and intervention costs. Numerical simulations show that combined preventive, treatment, and awareness measures substantially reduce infection peaks and accelerate recovery. This framework extends classical models and supports the WHO’s “Defeating Meningitis by 2030” roadmap, offering practical insights for designing cost-effective and sustainable control strategies in resource-limited health systems.
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