The Dutch regional construct for the medical assistance in accidents and disasters (GHOR) was established more than twenty years ago to play an important coordinating role in medical crises. The GHOR’s right to exist was already a serious point of discussion before the COVID-19 crisis. By 2020 the Evaluation committee of the Safety Regions Act had concluded that the GHOR was of no added value. Its performance during the COVID-19 crisis did not lead to a different perspective. This article shows that the GHOR has quite a different view of its own role as compared to other medical emergency and non-emergency services. This can be explained from a multi-actor perspective. The GHOR was operating within the planning and consultation arena while the other medical emergency and non-emergency services were functioning within the operational arena to combat the crisis.

This study presents the results of the first nationwide research on the preventive and signaling role of secondary education in serious and organized crime. The findings indicate that most educational staff encounter student involvement in serious and organized criminal activities. Results show that educational personnel are aware of their responsibility but also highlight the lack of training, information, and specific protocols for recognizing and addressing relevant signals. Additionally, the signals they need to look out for are often general and may also indicate other issues, making recognition and interpretation challenging.

This article assesses whether the ambient population is a more suitable population-at-risk measure for crime types with mobile targets than residential population. Specifically, the potential use of ambient population as a crime rate denominator and predictor for predictive policing models is evaluated, using mobile phone data (n = 595,858,852 raw data points) as a proxy. The results show that ambient population correlates more strongly with crime than residential population. Crime rates based on ambient population designate different problem areas than crime rates based on residential population. The prediction performance of predictive policing models can be improved by using ambient population instead of residential population. These findings support that ambient population is a more suitable population-at-risk measure, as it better reflects the underlying dynamics in spatiotemporal crime trends.