PREMONITIONModelling Fire Risk Behaviours and Attitudes in the

South Yorkshire Region to improve the Identification of

Areas at Risk of Fire in the Community

Steve FletcherSteve Fletcher

South Yorkshire Fire & Rescue

and

Dermot Breslin

University of Sheffield

• An Agent-Based Model (ABM) simulates behaviours of

individuals within a community over time

• An ABM includes the interact and connection between

individuals (i.e. how individuals influence each other)

What is an AgentWhat is an Agent--Based ModelBased Model

•Agents behaves

according to ‘simple’ according to ‘simple’

rules relating to

behaviours under study

• Over time patterns of

behave emerge and

evolve within the

community of agents

• Distribution of Mosaic

type at household level

for Gleadless Valley

region of Sheffield

• Historical data relating to

smoking, alcohol

consumption in region

What are the Model Inputs for What are the Model Inputs for

Premonition?Premonition?

• Statistical data on fire

risk behaviours for

different Mosaic types

• Incident reports for

Gleadless Valley region

• Home Safety Check data

for Gleadless Valley

region

Assessment of

Risk

Household

Modelling Fire Risk Behaviours Modelling Fire Risk Behaviours

and Assessments of Riskand Assessments of Risk

Mosaic UK classification group

Daily

Household

BehavioursMosaic Type

Influence of

others

Fire Risk

Behaviours

How do agents influence each How do agents influence each

otherother

Influence of

Family

Influence of

Social Network

Influence

Influence of

Peers

Influence of

Neighbours

Influence of

FriendsInfluence

of community group

leaders

The Effect of Social Connectivity The Effect of Social Connectivity

and Individual Behavioursand Individual Behaviours

Framingham Studies in

Massachusetts on effect of social

connectedness on obesity,

smoking, happiness (Nicholas

Christakis and James Fowler,

Harvard Medical School, 2007-8)

Key Benefits and DeliverablesKey Benefits and Deliverables

• Improved understanding of research on fire risk behaviours nationally, and

use of historical data relating to changing community behaviours locally.

• By predicting changing patterns of high risk behaviours in the Sheffield

region, it can be used by SYFR as a key tool in strategic and operational

planning activities, such as scenario planning, the exploration of different

preventative intervention strategies, and the optimisation of resource allocation.

• Improved protection of vulnerable

communities by better identification of

effective interventions in areas at high risk.

While the initiative will be initially

implemented within South Yorkshire, it has

the potential to be extended to regional and

national levels.