Effect of density dependence on coinfection dynamics

Area of Science:

• Epidemiology
• Mathematical Biology
• Population Dynamics

Background:

• Coinfecting diseases pose complex public health challenges.
• Understanding disease dynamics in relation to population size is crucial for effective control strategies.

Purpose of the Study:

• To develop a compartmental SIR model for coinfecting diseases.
• To analyze how carrying capacity (K) influences disease dynamics, complexity, and pathogen invasion.
• To explore the relationship between habitat size and infection complexity.

Main Methods:

• Developed a compartmental SIR model for two coinfecting diseases.
• Utilized bifurcation analysis to study the system's behavior.
• Investigated transition diagrams for locally stable equilibrium states as a function of carrying capacity (K).

Main Results:

• Disease dynamics become more complex with increasing carrying capacity (K).
• Pathogen invasion is dependent on carrying capacity (K).
• Identified four distinct scenarios where infection complexity arises with growing K, particularly for specific reproduction number values.

Conclusions:

• Carrying capacity (K) significantly shapes disease progression and complexity.
• Larger population groups (higher K) lead to more intricate infection dynamics.
• The model provides insights into disease management strategies by considering habitat size and population grouping.