When a fire breaks out, every minute matters. That is why firefighters always strive to get to the scene as quickly as possible. Yet the precise influence of response time on the eventual damage had long remained unclear. New research by Vrije Universiteit Amsterdam, Erasmus University, the Rotterdam-Rijnmond Veiligheidsregio and the Netherlands Instituut voor Publieke Veiligheid confirms the connection. “We all suspected that slower arrival times would lead to more damage, but this is the first time we have been able to prove it conclusively,” says mathematician Caroline Jagtenberg of Vrije Universiteit Amsterdam.
Together with colleagues, she analysed thousands of fire incidents from 2018–2022. The results show that the likelihood of major damage increases almost linearly with every extra minute it takes the fire brigade to arrive. On average, the chance of serious fire damage rises by about 1.2% per minute. Once response time exceeds ten minutes, every additional minute becomes critical: the risk of total loss grows even more sharply, meaning fire damage escalates minute by minute.
Every minute counts in a fire
The follow-up question, of course, is how firefighters can ensure they reach incidents as quickly as possible. Jagtenberg and her colleagues make several recommendations. To shorten response times, a smart distribution of fire stations is needed, for example determined with mathematical models. Special Intervention Vehicles (SIVs) may also provide a solution: these can be deployed more quickly with fewer crew members than the standard six. In some regions, the fire service is already experimenting with them. This allows for a much faster response, but it also raises the question of how effective the smaller vehicles are. Jagtenberg and her colleagues hope to explore this in future research. Finding the right balance between speed and operational strength will therefore remain an important focus for the fire service of tomorrow.
You can read the full study here, and listen to a podcast (made in collaboration with AI) in which the research is discussed in more detail.