Abstract
Pneumonia and Listeriosis are significant public health concerns, both individually and as co-infections, particularly in vulnerable populations such as the elderly, immunocompromised individuals, and infants. Using a mathematical modeling approach, this study explores the epidemiological impact of Pneumonia–Listeriosis co-infection within human populations. By developing a comprehensive model incorporating the transmission dynamics of both diseases, we aim to understand the synergistic effects of co-infection on disease prevalence, morbidity, and mortality. Mathematical analysis was established, encompassing the transmission threshold calculation, calculated equilibrium points, and local stability. The model also assesses the influence of key parameters, such as transmission rates, recovery rates, and co-infection interactions, on the overall disease burden. Sensitivity analysis is performed to identify the most critical factors driving the spread of the co-infection. Furthermore, we include the optimal control interventions to minimize the spread of Pneumonia–Listeriosis co-infection and the costs associated with implementing control. Our findings provide valuable insights into the complexities of managing co-infections and highlight the importance of targeted interventions to reduce the public health impact of Pneumonia–Listeriosis co-infection. The results of this study inform public health strategies aimed at mitigating the dual burden of these infections, thereby improving patient outcomes and reducing healthcare costs.
| Original language | English |
|---|---|
| Article number | 197 |
| Journal | International Journal of Dynamics and Control |
| Volume | 13 |
| Issue number | 5 |
| DOIs | |
| State | Published - May 2025 |
Scopus Subject Areas
- Control and Systems Engineering
- Civil and Structural Engineering
- Modeling and Simulation
- Mechanical Engineering
- Control and Optimization
- Electrical and Electronic Engineering
Keywords
- Co-infection modeling
- Listeriosis/Pneumonia
- Sensitivity analysis
- Simulations