A paper titled ‘Road safety forecasts in five European countries using structural time-series models‘, co-authored by Constantinos Antoniou, Eleonora Papadimitriou and George Yannis is now published in Traffic Injury Prevention. The objective of this research is toapply structural time series models for obtaining reliable medium- to long-term forecasts of road traffic fatality risk using data from 5 countries with different characteristics from all over Europe(Cyprus, Greece, Hungary, Norway, and Switzerland). Two structural time series models are considered: (1) the local linear trend model and the (2) latent risk time series model. Furthermore, a structured decision tree for the selection of the applicable model for each situation (developed within the Road Safety Data, Collection, Transfer and Analysis

[DaCoTA] research project, co-funded by the European Commission) is outlined. The modeling process included the model selection, the introduction of intervention variables and the development of mobility scenarios. The forecasts using the developed models appear to be realistic and within acceptable confidence intervals. The proposed methodology is proved to be very efficient for handling different cases of data availability and quality, providing an appropriate alternative from the family of structural time series models in each country.