Spatio-temporal systems with heterogeneity in their structure and behavior have two major problems. The first one is that such systems extend over very large spatial and temporal domains and consume a lot of resources to simulate that they are infeasible to study with current platforms. The second one is that the data available for understanding such systems is limited. This also makes it difficult to get the data for validation of their constituent processes while simultaneously considering their global behavior. For example, the valley fever fungus considered in this dissertation is spread over a large spatial grid in the arid Southwest and typically needs to be simulated over several decades of time to obtain useful information. It is also hard to get the temperature and moisture data at every grid point of the spatial domain over the region of study. In order to address the first problem, we develop a method based on the discrete event system specification which exploits the heterogeneity in the activity of the spatio-temporal system and which has been shown to be effective in solving relatively simple partial differential equation systems. The benefit of addressing the first problem is that it now makes it feasible to address the second problem.We address the second problem by making use of a multilevel methodology based on modeling and simulation and systems theory. This methodology helps us in the construction of models with different resolutions (base and lumped models). This allows us to refine an initially constructed lumped model with detailed physics-based process models and assess whether they improve on the original lumped models. For that assessment, we use the concept of experimental frame to delimit where the improvement is needed. This allows us to work with the available data, improve the component models in their own experimental frame and then move them to the overall frame. In this dissertation, we develop a multilevel methodology and apply it to a valley fever model. Moreover, we study the model's behavior in a particular experimental frame of interest, namely the formation of new sporing sites.

Indiana University-Purdue University Indianapolis (IUPUI) / Survivors of sexual assault make difficult privacy management decisions regarding their experiences, particularly in romantic relationships where physical intimacy makes these sensitive disclosures even more complex. As fever is an indicator of illness and a part of healing from the illness, disclosure can be an indicator of underlying disturbance and a part of the restorative process. Additionally, communication privacy management (CPM) theory considers ownership, control, and turbulence to illustrate how private information is regulated. Through qualitative, semi-structured interviews (n=19) and a phronetic iterative approach to data analysis, I examined the ways survivors of sexual assault managed their private information regarding their experiences in a romantic relationship and if disclosure relieved any psychological distress of the survivor. Results of this study offer insight into the ways participants controlled their personal information through the privacy management process; the establishment of boundaries surrounding ongoing disclosures; and the emotional effect of various privacy management strategies on participants, their partners, and the relationship. Reaching across theoretical concepts, this research offers a comprehensive understanding of the factors salient when managing private information regarding sexual assault. This research also provides practical applications for considering the influence of various privacy management approaches and their influence on the physical and psychological health of the survivor and the health of the relationship.