We live in an era of global change, where emerging infectious diseases such as Ebola, Zika, bird flu, and white nose syndrome are affecting humans, wildlife, and domesticated species at an increasing rate. To understand and predict the dynamic spread of these infectious agents and other symbionts through host populations and communities, we need dynamic mathematical models that accurately portray host-symbiont transmission. But transmission is an inherently difficult process to measure or study, because it is actually a series of interacting processes influenced by abiotic and biotic factors at multiple scales, and thus empirical tests of the transmission function within epidemiological models are rare. Therefore, in this dissertation, I explore factors at the individual, population, and community-levels that influence host contact rates or symbiont transmission success in a common snail-symbiont system, providing a detailed description of the multi-faceted nature of symbiont transmission. From a review of the ecological literature, I found that most models assume that transmission is a linear function of host population density, whereas most empirical studies describe transmission as a nonlinear function of density. I then quantified the net nonlinear transmission-density relationship in a system where ectosymbiotic oligochaetes are directly transmitted among snail hosts, and I explored the ecological mechanisms underlying the nonlinear transmission-density relationship observed in the field via intraspecific transmission success and contact rate experiments in the laboratory. I found that the field results could be explained by heterogeneity in transmission success among snails with different characteristics and nonlinear contact-density relationships caused by non-instantaneous handling times. After I 'unpacked'population-level transmission dynamics into those individual-level mechanistic processes, I used this same approach to examine higher-level ecological organization by describing the mechanistic underpinnings of interspecific or community-level transmission in the same snail-symbiont system. I found that low interspecific transmission rates in the field were the product of opposing interactions between high population densities, high prevalences of infection, and very low interspecific transmission success caused by strong symbiont preferences for their current host species. Unpacking transmission in this way resulted in one of the most detailed empirical studies of transmission dynamics in a wildlife system, and yielded many surprising new insights in symbiont ecology that would not have been discovered with a purely phenomenological or holistic view of transmission. Though simple, linear, and holistic epidemiological models will always be important tools in disease ecology, 'unpacking'transmission rates and adding heterogeneity and nonlinearity to models, as I have done here, will become increasingly important as we work to maximize model prediction accuracy in this era of increased disease emergence.