COST-EFFECTIVENESS AND OPTIMAL CONTROL ANALYSIS OF MALARIA-TYPHOID CO-INFECTION DYNAMICS AMONG POPULATION SETTINGS IN IDAH

Malaria and typhoid fever are important causes of febrile illness in sub-Saharan Africa, where overlapping clinical manifestations complicate diagnosis, treatment and disease control. This study integrates diagnostic evaluation, mathematical modelling, optimal control and cost-effectiveness analysis to examine malaria–typhoid co-infection in Idah population settings, Kogi State, Nigeria. A diagnostic dataset of 1,000 febrile patients was analysed using expert microscopy/PCR as the malaria reference standard and blood culture with compatible clinical presentation as the typhoid reference standard. Malaria prevalence was 42% and typhoid prevalence was 18%. Malaria RDT recorded 94.05% sensitivity, 91.03% specificity and 92.30% accuracy, while microscopy recorded 90.00%, 97.07% and 94.10%, respectively. For typhoid, Widal test sensitivity, specificity and accuracy were 76.11%, 68.05% and 69.50%; corresponding values for blood culture were 65.00%, 99.02% and 92.90%, and stool culture 57.78%, 98.05% and 90.80%. A deterministic malaria–typhoid co-infection model incorporating environmental transmission and diagnostic error was formulated. Five controls—vector control, improved malaria diagnosis, improved typhoid diagnosis, treatment and environmental sanitation—were evaluated using Pontryagin’s Maximum Principle and fourth-order Runge–Kutta simulation over 365 days. Among the fixed intervention strategies, the combined application of all five controls was the most cost-effective, with an incremental cost-effectiveness ratio of approximately ₦426.45 per additional burden unit averted and 610,904.77 burden units averted. The numerical optimal-control strategy achieved 570,056.79 burden units averted at an estimated annual cost of ₦1.106 billion and was cost-saving relative to the diagnosis-plus-treatment strategy. The findings support integrated diagnostic, treatment, vector and environmental interventions as an economically efficient approach to controlling malaria–typhoid co-infection.