In this paper, I examine design documents from three different ICT design and development projects. I argue that they present intersecting visions of sustainability entailing the wide-spread use of ICT, describe the properties of users compatible with such ICT, and provide ways of judging the users. In the design documents, the inhabitants are made individually responsible for living sustainably, and surveillance is positioned as integral to this future with the help of ICT. Underlying the visions, I identify a translation process that captures the traces of the inhabitants' lives, classifies them according to different criteria of sustainable living, and returns them to the tapestry of everyday life to convince the users to behave differently. In the discourses of these documents, surveillance translates the traces, and the translations exert new pressures on existing power relations.

Information and communication technologies are not value-neutral. I examine two domains, public health surveillance and sustainability, in five papers covering: (i) the design and development of a software package for computer-assisted outbreak detection; (ii) a workflow for using simulation models to provide policy advice and a list of challenges for its practice; (iii) an analysis of design documents from three smart home projects presenting intersecting visions of sustainability; (iv) an analysis of EU-financed projects dealing with sustainability and ICT; (v) an analysis of the consequences of design choices when creating surveillance technologies. My contributions include three empirical studies of surveillance discourses where I identify the forms of action that are privileged and the values that are embedded into them. In these discourses, the presence of ICT entails increased surveillance, privileging technological expertise, and prioritising centralised forms of knowledge.

A critical investigation into computational models developed for studying the spread of communicable disease is presented. The case in point is a spatially explicit micro-meso-macro model for the entire Swedish population built on registry data, thus far used for smallpox and for influenza-like illnesses. The lessons learned from a software development project of more than 100 person months are collected into a check list. The list is intended for use by computational epidemiologists and policy makers, and the workflow incorporating these two roles is described in detail.

Background: In computer supported outbreak detection, a statistical method is applied to a collection of cases to detect any excess cases for a particular disease. Whether a detected aberration is a true outbreak is decided by a human expert. We present a technical framework designed and implemented at the Swedish Institute for Infectious Disease Control for computer supported outbreak detection, where a database of case reports for a large number of infectious diseases can be processed using one or more statistical methods selected by the user.

Results: Based on case information, such as diagnosis and date, different statistical algorithms for detecting outbreaks can be applied, both on the disease level and the subtype level. The parameter settings for the algorithms can be configured independently for different diagnoses using the provided graphical interface. Input generators and output parsers are also provided for all supported algorithms. If an outbreak signal is detected, an email notification is sent to the persons listed as receivers for that particular disease.

Conclusions: The framework is available as open source software, licensed under GNU General Public License Version 3. By making the code open source, we wish to encourage others to contribute to the future development of computer supported outbreak detection systems, and in particular to the development of the CASE framework.