Multi-Resistant Bacterial Infection Surveillance Using A Graph Database With Spatio-Temporal Information

Some of epidemiologists' efforts in dealing with multi-resistant bacterial infections acquired in healthcare settings focus on tracing patient's activities, carrying out a contact analysis, and identifying the main risk factors that lead the appearance of these infections. Most contact analysis studies assume information is stored in conventional relational databases. To date, little attention has been paid to other storage paradigms. This paper explores the potential of graph databases to establish the complex relations required to compute contact analysis. We discuss the advances in modelling of the temporal and the spatial information of the Electronic Health Record that has to be introduced in the graph database. In this position paper we propose three points for discussion: advances in formal modelling, specific algorithms for graph analysis, and visualisation tools.