Following the 2009 bushfires that claimed 173 lives, the Victorian Royal Commission concluded that “a more comprehensive policy is required – one that better accommodates the diversity of bushfires and human responses”.

Many factors impact how communities respond to emergencies and warnings. These include individuals' demographic profile, preparedness, preferences towards staying or leaving, exposure and receptivity to warnings and visual cues, access to a vehicle, severity and progression of the hazard, and practical factors such as power or water failure.

We present a novel approach to predicting community response to an emergency using a simulation model called CERM (Community Emergency Response Model). CERM can predict how people will respond to different hazards, when they will leave, and where they will go. CERM can be used to assess measures such as warning schedules, adequacy of shelters, and traffic management.

The cognitive risk model that drives CERM has three dimensions: threat, representing the perceived threat of the incident; uncertainty, representing the uncertainty of the threat impacting the individual; and vulnerability, representing the individuals’ perceived level of vulnerability to the threat (risk of life).

Scenario inputs include severity and progression of the incident, warnings schedule, resource failures, and the presence or absence of emergency services in the region. CERM characterises different community types and combines this with Census data to simulate the behaviour of individuals and families throughout the day. For each incident and individual, simulated factors are correlated to estimate the level of threat, uncertainty and vulnerability, and thus estimate their likely response.

We validated CERM using two independent historical bushfires affecting different types of communities and show that CERM can predict the behavioural response of each community to a high level of accuracy. To our knowledge, CERM is the first simulation model that can accurately predict community response to emergencies.