Risk assessment is a fundamental part of a fire department organization and deployment of resources.

Estimating the risk means determining the likelihood of incidents, the consequences that incidents can have on the community, and the impact on the responding agency.

The importance of risk assessment is recognized the National Fire Protection Association (NFPA®), which provides baseline standards for the reduction of the risk and the mitigation of consequences and impact.

The analysis of demographic and socio-economic data enables quantitative forecasts of the risk. Listing potential risk factors is a good starting point. However, not all risk factors may be relevant for every community. Even within the same community, different factors can have a different impact on the risk.

The IAFF has developed a statistical approach to predict the likelihood of incidents based on the combination of demographic and economic variables with the incident statistics provided by fire departments. The advantage of this method is that it helps to predict the future likelihood of incidents, even in areas of the community which are evolving or developing, and determines what factors are driving the number of incidents.

Using this information, fire departments can make more informed decision on the deployment of resources, as well as on prevention measures to adopt to reduce the risk. With vast amounts of data becoming increasingly more accessible, machine learning methods can be applied in the future, allowing more precise predictions, even for communities that do not have incident statistics available.

Speaker Bio

Francesco De Bernardis received his PhD in Physics and Astronomy from the University of Rome, Italy, in 2010, and subsequently worked as a research associate at the University of Irvine (California) and Cornell University. Since 2017, he has worked as a Data Research Analyst with the International Association of Fire Fighters. He develops software to clean and organize data, forecast fire departments’ performance, and conducts GIS and workload analysis. He is part of the team that developed the risk assessment method currently used by the IAFF.