Learned behavioral avoidance can alter outbreak dynamics in a model for waterborne infectious diseases

Area of Science:

• Ecology
• Epidemiology
• Behavioral Ecology

Background:

• Animals often exhibit avoidance behaviors when exposed to diseases, such as frogs avoiding areas with chytridiomycosis pathogens.
• Chytridiomycosis, a fungal disease, has caused significant amphibian population declines globally, making it a critical case study for disease-driven behavioral dynamics.

Purpose of the Study:

• To investigate the epidemiological consequences of animal avoidance behavior in response to waterborne infectious diseases using mathematical models.
• To compare the outbreak dynamics of innate (from birth) versus learned (post-infection survival) avoidance behaviors.
• To assess the impact of management interventions aimed at inducing learned avoidance.

Main Methods:

• Development of compartmental ordinary differential equation (ODE) models to simulate disease transmission and avoidance.
• Application of dynamical systems theory, including calculation of the basic reproduction number (R0), equilibrium stability analysis, and bifurcation analysis.
• Parameterization of models using data from chytridiomycosis in amphibians to simulate real-world scenarios.

Main Results:

• Disease persistence (R0 > 1) is possible with learned avoidance but not with innate avoidance.
• Management strategies to induce learned avoidance can inadvertently lead to disease persistence.
• Learned avoidance models exhibit complex bifurcations absent in innate avoidance models, with persistence less likely for high-mortality diseases like chytridiomycosis.

Conclusions:

• Learned avoidance behavior can create conditions for disease persistence, a scenario not observed with innate avoidance.
• While management can induce learned avoidance, it may increase disease persistence risk, especially for diseases with lower mortality rates.
• Understanding the nuances of innate versus learned avoidance is crucial for predicting disease dynamics and designing effective conservation strategies.