Stochastic within-host dynamics and climate-sensitive traits generate predictable patterns of variation in disease...

Area of Science:

• Ecology and Evolutionary Biology
• Epidemiology
• Climate Change Biology

Background:

• Climatic variables significantly influence host-pathogen interactions, especially in temperature-sensitive ectotherms.
• Understanding temperature-driven variations in host susceptibility and pathogen replication is vital for predicting disease dynamics under global change.
• Limited research exists on how temperature gradients affect inter-individual epidemiological traits.

Purpose of the Study:

• To develop a mathematical model exploring how thermal mismatches and within-host stochasticity influence infection outcomes in ectotherms.
• To investigate the generation of predictable variation in disease dynamics across thermal gradients.
• To provide a theoretical framework for ectotherm disease modeling under climate change.

Main Methods:

• Development of a novel mathematical model simulating within-host dynamics.
• Incorporation of stochasticity in within-host processes.
• Simulation of thermal mismatches between host immunity and pathogen replication traits across temperature gradients.

Main Results:

• Varying thermal optima for host immunity and pathogen replication, coupled with stochasticity, generated significant variation in infection outcomes.
• Disease variability was low when temperatures favored either host or pathogen, but high when their performance was similar.
• Magnitude of variation, measured by entropy, showed predictable patterns linked to host-pathogen thermal mismatches.

Conclusions:

• Interactions between trait thermal mismatches and within-host stochasticity offer a robust theoretical framework for ectotherm disease models.
• This approach can enhance predictions of epizootic and epidemic dynamics in ectothermic organisms facing climate change.
• The findings are particularly relevant for understanding disease impacts in vulnerable marine ecosystems.