Novel Numerical Estimates of the Pneumonia and Meningitis Epidemic Model via the Nonsingular Kernel with Optimal Analysis

In this article, we investigated a deterministic model of pneumonia-meningitis coinfection. Employing the Atangana-Baleanu fractional derivative operator in the Caputo framework, we analyze a seven-component approach based on ordinary differential equations (DEs). Furthermore, the invariant domain, disease-free as well as endemic equilibria, and the validity of the model's potential results are all investigated. According to controller design evaluation and modelling, the modulation technique devised is effective in diminishing the proportion of incidences in various compartments. A fundamental reproducing value is generated by exploiting the next generation matrix to assess the properties of the equilibrium. The system's reliability is further evaluated. Sensitivity analysis is used to classify the impact of each component on the spread or prevention of illness. Using simulation studies, the impacts of providing therapy have been determined. Additionally, modelling the appropriate configuration demonstrated that lowering the fractional order from 1 necessitates a rapid initiation of the specified control technique at the largest intensity achievable and retaining it for the bulk of the pandemic's duration.

Automated summary

This article investigates a deterministic model of pneumonia-meningitis coinfection using the Atangana-Baleanu fractional derivative operator. The study analyzes a seven-component approach based on ordinary differential equations (DEs) and examines the validity of the model's potential results. The findings suggest that the modulation technique employed effectively reduces the proportion of incidences in various compartments. The use of the next generation matrix to assess equilibrium properties and sensitivity analysis to classify the impact of each component on the spread or prevention of illness are also discussed.