We have developed and maintain several web platforms related to the CIMPLEX developments and utilizing its results. Our main example for social contagion was infection, and the leading example of that is influenza. Hence we present a number of flu related tools but not only those.

Influenzanet Influenzanet is a Europe-wide network to monitor the activity of influenza-like-illness (ILI) with the aid of volunteers via the internet. It is operational in ten countries. In contrast with the traditional system of sentinel networks of mainly primary care physicians, Influenzanet obtains its data directly from the population. This creates a fast and flexible monitoring system whose uniformity allows for direct comparison of ILI rates between countries. One can click on each country to visit the respective national platform.

GleamVIZ   http://www.gleamviz.org The latter is an online tutorial about modeling diseases and using the GLEAM simulation environment (and the GleanVIZ tool) to analyze the spread of influenza-like diseases around the globe. After giving a short overview over the background of disease simulation and the GLEAM as well as the CIMPLEX research project, we will first get a look at developing a disease model describing an influenza-like disease. Having developed the model and becoming familiar with it we will jump into the GLEAMviz simulator, running our own simulations based around self defined disease models and analyzing the results. In the last chapter of this tutorial there will be a short perspective about real world applications of such simulations and additional simulation exercises.   A link to the main ETH grippenet website (in German). Grippenet is the Swiss component of Influenzanet, supported by the GrippeNET App for data acquisition,.

S-index This is a link to a tool analyzing social influence in a different domain, scientific citations. It is a server where we can look up any active author that has at least one publication,  which has been cited at least once (assuming it is in the web of science dataset). We then get a picture of their network of co-authors and then their performance metrics according to the social citation pattern described in the PHD thesis “Networks and individual success in science”, by C. Schultz, and will be submitted as a manuscript. The proposed citation impact indicator is a useful tool to help researchers and policy makers filter information in a more objective way. For each profile, statistics generated from the collaboration and citation network are displayed as charts and network visualizations. We developed the network layout to visualize the network position of an individual by preserving both local and global structural features of a network. Such a layout more clearly captures the influence and vulnerability of an individual to network-driven spreading processes. For the network visualization on the web application we pre-compute optimal node positions for all authors on a computing cluster. With each author request, we then further optimize the node positions such that they better correspond to the effective network distance from the focal author. Thereby we can interactively navigate through a network consisting of millions of nodes.