The current work addresses the technical and social issues that must be considered when assessing the probability of infectious disease occurrence of natural or man-made origins, within a nation state or across the globe. The technical aspects of the problem relate to the ability to detect potentially subtle changes in the level of threat agents in an environment, the susceptibility of the host, and environmental conditions rendering the host vulnerable to infection. In order to determine an increase in disease emergence, it is necessary to establish a baseline of normal disease incidence in a population, the concentration of pathogens in each environmental region, and the presence of non-pathogenic organisms that are genomically or proteomically similar to pathogens. Once baselines are established for these factors, multiplexed sensors and data fusion technologies can be used to relate changes in the concentration of agents or in host susceptibility to the emergence of clinical symptoms in a community. One premise of this paper is that emergent disease is neither a function of infectious agents alone nor of susceptibility of the human or livestock target alone, but rather it is a probabilistic event dependent on multiple factors including the interaction between the pathogen and the host target. The probabilistic assessment of emergent disease requires large databases, deployed sensors, data fusion, and autonomous rapid decision making capabilities. The extensive deployment of pervasive surveillance systems can cause societal concerns regarding the balance between assuring wellness in a population while simultaneously respecting the privacy of individuals. Because emergent pandemic disease is a relatively low probability event, it is probable that a significant time lapse will occur between the gathering of information from the distributed sensors and the actual realization of pandemic disease. During this interval, societal perceptions may instigate public concern over compromised privacy, because benefits from the sensor deployment may not yet be realized. Possible adverse affects include changes in insurance rates of individuals, loss of employment opportunities, and other unanticipated negative consequences resulting from widespread data acquisition. The goal, however, of maintaining the wellness of society as a whole will require thoughtful balance between the potential loss of individual privacy and maintaining the wellness of the community.