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Severe natural or man-made disasters that occur in urban areas often require evacuation measures to protect or rescue the population. In crisis situations, different kinds of knowledge are necessary to get insight in the consequences of the proposed set of measures. In addition, there are typically many different parties involved in the decision making process. These decision makers can be supported by simulation models that assist in assessing and predicting the emergency situation and assist in the development of effective evacuation plans. There are currently many existing (simulation) models available for evacuation planning. However, the population data which is an important input parameter for the models, usually consists of generic or even fictive information. The mixed reality project “Reality Check”, which is part of the Dutch research program “Flood Control 2015”, aims to feed more reliable data into an evacuation model. This input data can be either static data, for example extracted from population registers, or dynamic real-time data. Both types of data improve the situational awareness of the decision makers dealing with a calamity and provide them with better simulation results to assess their options. The “Reality Check” tool combines several population databases, a road database and a scientific evacuation model. The tool has been realized using the MiReCol architecture (Mixed Reality for Collaboration). MiReCol enables the integration of scenarios, protocols, (scientific) models and data sources, in order to provide decision makers with real-time output from predicting models during crisis situations. In the MiReCol architecture, all components are linked through a network data bus, and web services are used to exchange information between data sources, evacuation models, and assessment or presentation tools. The “Reality Check” tool makes the knowledge and information from different sources and models available to all involved participants.

Systemic sclerosis (SSc) is an autoimmune disease characterized by fibrosis of the skin and internal organs that leads to profound disability and premature death. To identify new SSc susceptibility loci, we conducted the first genome-wide association study in a population of European ancestry including a total of 2,296 individuals with SSc and 5,171 controls. Analysis of 279,621 autosomal SNPs followed by replication testing in an independent case-control set of European ancestry (2,753 individuals with SSc (cases) and 4,569 controls) identified a new susceptibility locus for systemic sclerosis at CD247 (1q22-23, rs2056626, P = 2.09 x 10(-7) in the discovery samples, P = 3.39 x 10(-9) in the combined analysis). Additionally, we confirm and firmly establish the role of the MHC (P = 2.31 x 10(-18)), IRF5 (P = 1.86 x 10(-13)) and STAT4 (P = 3.37 x 10(-9)) gene regions as SSc genetic risk factors.