Picturing Public Health Surveillance: Tracing the Material Dimensions of Information in Ontario’s Public Health System
MetadataShow full item record
The aim of this dissertation is to explore public health surveillance from a surveillance studies perspective. The public health system in Ontario, Canada, provides an ideal setting for such exploration, especially because of initiatives that have been undertaken in the wake of the 2003 outbreak of Severe Acute Respiratory Syndrome (SARS). Post-SARS, local public health practice in Ontario has been increasingly overtaken by a system-wide imperative that seeks to transform surveillance through investment in large-scale, information technology (IT). By critiquing the dominant conception of information in social scientific, public health and medical care discourse, and by exploring the increasing integration of large-scale IT into public health surveillance practice, this dissertation considers the uncertain trade-offs involved in the contemporary movement towards large-scale, IT-mediated public health surveillance systems. The theoretical framework that guides this line of inquiry emerges out of a Deleuzian-Latourian tradition in surveillance studies. This framework foregrounds the material assemblages, the network of people, machines, microbes, maladies, organizations, and so on, that make public health surveillance possible. Material assemblages tend to be submerged from view, even marginalized, by large-scale, IT-mediated surveillance systems. Such systems strive to immaterialize information. They are organized according to an immaterial conception of information. This arrangement fosters the marginalization of the material dimensions of information. In order to empirically specify the heterogeneity of the marginalized material assemblages that make public health surveillance possible, 64 semi-structured, open-ended interviews were conducted with public health professionals and patients. The main findings of this dissertation are explained using the example of communicable-disease surveillance, and particularly HIV/AIDS surveillance. These findings highlight the systemic nature of marginalization that accompanies the increasing automation of public health surveillance. They suggest the need to question whether large-scale, IT-mediated surveillance is optimally configured, not merely for the challenges posed by disease, but also for the broader provision of public health services.