This research will examine the epidemiological implications and evolution of multiple modes of disease transmission. Using simulation and theoretical analysis, general strategic models describing vector and aerial transmission in spatially extended populations will be developed concurrently with models applicable to anther-smut disease, a model system for studies of disease ecology in natural populations. Adaptive dynamics theory will be used to investigate how transmission mode evolves in response to different life history and epidemiological features. To apply that theory to a real-world system, this research will measure contributions of aerial and vector transmission in nature, study genetic variation and covariation in transmission mode in host populations, and look for the signals of transmission mode in natural populations where there is long-standing data on density and disease prevalence. This disease system is well characterized ecologically and genetically, and is a highly tractable model system allowing large and directed experimental studies of transmission modes in natural populations. A key advance is the formulation of transmission functions to take into account host spatial distributions, including the concept of a perception kernel to study vector transmission. Furthermore, the work breaks new ground by investigating the evolution of transmission mode itself, rather than the evolutionary consequences of transmission mode for other host and pathogen traits such as virulence. This study emphasizes that the evolution of transmission mode is a co-evolutionary process involving the interplay of both host and pathogen traits, as well as the biotic and abiotic environmental context.
Although transmission is a central concept in disease biology, the consequences of multiple transmission modes has only been extensively studied in terms of vertical vs. horizontal transmission. This will be one of the first studies to ask how the presence of multiple routes of horizontal transmission impact disease dynamics both in theory and in a real-world natural system.
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