Data Integrated Mathematical Modeling Approaches to Explore the Complexities of Amphibian Fungal Transmission Dynamics

Infectious diseases rapidly evolve into epidemics, presenting a significant risk to plants, wildlife, and humans. Empirical data analysis and mathematical modeling are essential for timely mitigation and preventative efforts. This methodology is crucial in developing comprehensive infectious disease control strategies. While human epidemics receive extensive attention, wildlife epizootics are often overlooked. This oversight has led to the extinction or substantial decline of numerous wildlife species owing to inadequate intervention measures. Therefore, the coupling of empirical data into mathematical models is crucial for enhancing the comprehension and control of wildlife diseases and epizootics to extend and improve conservation endeavors. As exemplary amphibians and infectious agents, we have considered eastern newt species of the salamander and emerging fungal pathogen, \textit{Batrachochytrium salamandrivorans (Bsal)} respectively. The primary objectives of this dissertation are: 1. Integrate experimental data into mathematical models to derive meaningful insights into disease control strategies. 2. Develop mathematical models to include life stages within disease dynamics to tailor control strategies. 3. Identify the dominant transmission pathway and significance of environmental factors. 4. Identify critical parameters in epizootic modeling and understand their impact on disease dynamics.\

We developed Susceptible-Exposed-Infected-Recovered (SEIR) type models using ordinary differential equations to study transmission dynamics of infectious fungal pathogens in amphibian wildlife. We focused on fungal pathogen transmission dynamics by taking into account direct contact and environmental transmission via zoospores in different life stages, initial exposure dosage, and temperatures. Understanding the relationship between environmental changes and disease dynamics is vital for identifying effective disease controls. By integrating experimental data into mathematical models, we were able to estimate and identify key parameters. Our approach enabled us to calibrate the model to reflect real-world scenarios better, enhancing its utility in targeted disease control strategies and further investigation. The first project in \autoref{Chapter2} highlights that adult eastern newts are super susceptible to \textit{Bsal}. With the availability of the data, we developed a more tailored life-stage-specific disease transmission model with multiple infective classes in the second project presented in \autoref{Chapter 3}. The disease transmission dynamics depended on the exposure dosage, infective classes, concentration of zoospores, and micro-predators that fed on these zoospores. Tracking the influence of zoospore concentration is crucial since it significantly affects disease dynamics, from the probability of disease transmission to the mortality rate of the infected individuals and disease spillover. This life-stage-specific analysis allowed for the development of more tailored intervention strategies. Through meticulous analyses of key epidemiological parameters, such as the basic reproduction number, dominant pathway, and exposure load, our study helps to develop focused and effective controlling strategies. For example, our analysis suggests that direct contact among newts is one of the key parameters in disease transmission dynamics. Therefore, efforts to minimize direct contact will be crucial for preventing the spread of the disease. This research proposes the potential for novel mitigation strategies to curb disease spread in wildlife by integrating real-world data with mathematical insights.

Embargo status: Restricted until 06/2025. To request the author grant access, click on the PDF link to the left.