Community emergency response model (CERM)

“Predict a better future”

COMMUNITY EMERGENCY RESPONSE MODEL (CERM)

Victorian Fire Services Commissioner & ISD Analytics

SimTecT 2013, Brisbane, Australia

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Simulait Online is like a real life “SimCity” application where businesses or Government can accurately predict and test strategies to influence the behavior of populations

Simulait Online uses a broad range of data sources to explain: What will consumers/communities do in the future? How can I change or influence what consumers/communities will do? What is the impact on my organisation or the community? What is the impact of different or new scenarios, strategies, policies, trends, marketing

campaigns, products, prices, competitive gaming, or future disruptive events?

Simulation-based Big Data Predictive Analytics approach: Applied to diverse consumer domains: water, energy,

emergency response, retail, transport, ... Applied globally: Australia, Europe, USA Cloud solution: on-demand access with a web browser

Simulait Online


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".

2009 Victorian Bushfires Royal Commission

The Challenge



Need to predict community behaviour given: The diverse and dynamic differences both within and between communities

E.g. demographic profile, level of preparedness & intentions Degree of motivation to act and types of behaviours

E.g. response to warnings & communication, safety messages and visual cues The uniqueness of each bushfire event The implementation of new untested strategies or interventions

E.g. warnings communicated – when, what and how Engagement with, and attitude towards, bushfire education and preparedness

Sufficient data exists to simulate and predict community behaviour.... just need

the right tools to manage the complexity and bring it all together!

Complex Problem



Community Emergency Response Model (CERM) can accurately predict the behavioural responses of communities to bushfires

What people will do and when: Stay, Leave or “Wait and see” (undecided) Where people will go: Neighbours, Designated shelter, Leave region or Open area Community responses to communications and bushfire warnings

Warning type /content, mediums, schedule, intensity Response to the arrival of the fire & its severity/size

The Solution: CERM


CERM was developed in partnership with a team of emergency services professionals and researchers, using extensive emergence response and health research on community response and behaviour

Can account for a broad range of factors influencing people’s response to emergencies Census and socio-demographic data Different levels of threat Fire spread and severity Household profile: e.g. preparedness, intentions, etc.. Warning schedules: mediums, timing, intensity The presence of emergency services Resource failures – e.g. water and power

Comprehensive Evidence-Based Model



Benefits of CERM include accuracy, functionality and accessibility

CERM was applied to two fires in Victoria (Churchill, 2009) and South Australia (Wangary, 2005) and demonstrated over 90% accuracy

Accuracy is not the only important aspect of CERM... it is the scenarios you can test and the insights you can gain

Simulait Online: on-demand access to CERM using a web-browser

Accurate, Functional, Accessible



Better predictions of community behaviour, and testing of interventions that can influence their behaviour, can support community risk assessment, safety planning, and enable realistic and effective policies

Application examples: Shelter options Warnings and community advice Traffic management Community risk assessment and protection

Strategies, policies and interventions to minimise community risk

CERM is applicable to other emergencies/disasters, as well as health policy Based on a human cognitive risk model when life is under threat

Inform Decisions, Save Lives


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CERM Insights



Warnings impacted on the community’s ability to respond appropriately

Some people were caught unaware on fire impact, and thus were unprepared Lack of warnings and communication regarding the fire progression and impact High speed of the fire

Some people that intended to stay changed their decision at the last moment Warnings and communications underestimated the severity of the fire Fire was more severe than people anticipated based on warnings Resulted in people leaving at the worst/unsafe time - when the fire arrived

Wangary Insights



Emergency Services Effect: identified unexpected factors that resulted in communities in different localities to respond differently

Presence of emergency services reduced the perceived threat by the community, resulting in most not making a decision to leave or stay

The wind then changed and the community were unprepared on fire impact

Late response limited the refuge options for those that decide to leave

0%

20%

40%

60%

80%

100%

Emergency services present . Effect of fire and emergency services on community response to the Churchill fire at Hazelwood South

Unaware/undecided Stay Leave Transitioning to Stay Transitioning to Leave

0%

20%

40%

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100%

Emergency services absent. Effect of fire and emergency services on community response to the Churchill fire at Hazelwood South


Churchill Insights



Applied the model to high risk communities to support safety planning

Focus was on how many people would leave and when for a small and large fire, to assist with traffic modelling and risk assessment Compared community response to a high severity (FFDI 50) and a catastrophic fire (FFDI

130) Looked at the response of different communities that were impacted at different times by

the fire and warnings

Planning for High Risk Communities



Comparison: Community A

Response timeline

Place of refuge

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0.0% 0.0%

17.0%

9.4%

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

Open area Neighbour Leave region Designated shelter

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Response timeline

Place of refuge

0%

20%

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60%

80%

100%

Prop

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3.6%

8.8%

33.8%

14.2%

0%

5%

10%

15%

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25%

30%

35%

40%


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High Severity Fire (FFDI 50) Catastrophic Fire (FFDI 130)

Embers, fire impact

Emergency Warnings

Impact & Emergency Warnings

Smoke visible, Watch & Act alerts

Smoke visible, Watch & Act alerts



Impact

10:00 16-Feb-13

11:00 16-Feb-13

12:00 16-Feb-13

12:59 16-Feb-13

14:00 16-Feb-13

15:00 16-Feb-13

15:59 16-Feb-13

17:00 16-Feb-13

18:00 16-Feb-13

18:59 16-Feb-13

20:00 16-Feb-13

21:00 16-Feb-13

22:00 16-Feb-13

0%

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60%

Transitioning to Leave Leave

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A

DE

Response timeline: Community AScenario • ‘Code red’ fire

(FFDI 130)• Up to 9 h warning

prior to impact• Predictions @ 30

min intervals

Predicted response• 60% of residents

left in 2 ‘waves’

Observations• 20% in 1st wave

‘early responders’ (most vulnerable)

• 40% in 2nd wave (less vulnerable)

Events

A 1100 Smoke visible

B 1130 Watch & Act

C 1500 Emergency Warnings

D 1800 Embers

E 1830 Fire

Smoke, Watch &

Act

B

Emergency Warnings

C



10:00 16-Feb-13

10:30 16-Feb-13

11:00 16-Feb-13

11:30 16-Feb-13

12:00 16-Feb-13

12:30 16-Feb-13

13:00 16-Feb-13

13:30 16-Feb-13

14:00 16-Feb-13

14:30 16-Feb-13

15:00 16-Feb-13

15:30 16-Feb-13

16:00 16-Feb-13

16:30 16-Feb-13

17:00 16-Feb-13

17:29 16-Feb-13

18:00 16-Feb-13

18:30 16-Feb-13

18:59 16-Feb-13

19:30 16-Feb-13

20:00 16-Feb-13

20:30 16-Feb-13

21:00 16-Feb-13

21:30 16-Feb-13

22:00 16-Feb-13

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Place of refuge: Community APredicted place of refugeEarly responders• Outside the region• Designated shelters

2nd wave also went• Neighbours• Open areas(i.e. ‘last-minute’ refuges)

Causal factorsWhy did 4% of residents seek refuge in open areas?1. Too vulnerable to defend

against a code red fire,2. No vehicle, and 3. No neighbours that

remained at home

Predicted place of refuge

1st wave

13% Outside region

7% Designated shelter

2nd wave

34% Outside region


9% Neighbour

4% Open area

Watch & Act alerts

Emergency Warnings



Response timeline

Place of refuge

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100%

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12.1%11.2%

18.9%

8.1%

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6%

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20%


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Response timeline

Place of refuge

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100%

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3.4% 3.6%

18.9%

8.2%

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2%

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20%


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Comparison: Community B

Embers & fire impact

Smoke visible, Emergency Warnings

Smoke visible, Emergency Warnings

Catastrophic Fire (FFDI 130)High Severity Fire (FFDI 50)

Embers, fire impact



Response timeline: Community BScenario • ‘Code red’ fire

(FFDI 130)• Only up to 1 h

warning prior to impact

• Predictions @ 30 min intervals

Predicted response• 53% of residents

left

Observations• At impact, only 3%

had left...• ...and 31% were

still preparing to leave

10:00 16-Feb-13

11:00 16-Feb-13

12:00 16-Feb-13

12:59 16-Feb-13

14:00 16-Feb-13

15:00 16-Feb-13

15:59 16-Feb-13

17:00 16-Feb-13

18:00 16-Feb-13

18:59 16-Feb-13

20:00 16-Feb-13

21:00 16-Feb-13

22:00 16-Feb-13

0%

20%

40%

60%

Transitioning to Leave Leave

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Events

A 1100 Smoke visible

B 1130 Emergency Warnings

C 1200 Embers & fire

Smoke, Emergency Warnings

Impact

AB

C



Place of refuge: Community BPredicted place of refugeUltimately:• Outside the region (19%)• Open areas (12%)• Neighbours (11%)• Designated shelters (8%)

Observations•A relatively high proportion went to open areas and neighbours (‘last-minute’ refuges)

•Consistent with having limited time to prepare

10:00 16-Feb-13

10:30 16-Feb-13

11:00 16-Feb-13

11:30 16-Feb-13

12:00 16-Feb-13

12:30 16-Feb-13

13:00 16-Feb-13

13:30 16-Feb-13

14:00 16-Feb-13

14:30 16-Feb-13

15:00 16-Feb-13

15:30 16-Feb-13

16:00 16-Feb-13

16:30 16-Feb-13

17:00 16-Feb-13

17:29 16-Feb-13

18:00 16-Feb-13

18:30 16-Feb-13

18:59 16-Feb-13

19:30 16-Feb-13

20:00 16-Feb-13

20:30 16-Feb-13

21:00 16-Feb-13

21:30 16-Feb-13

22:00 16-Feb-13

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Predicted place of refuge

19% Outside region


11% Neighbour

12% Open area

Emergency Warnings

Impact



Web-Based Access



Figure 1. An image of SOL, which shows the input grid used to configure community response simulations. Parameters are listed at the left hand side of the grid, where each component of the full parameter name is indented on a separate row. Time steps are listed along the top of the grid. A parameter's value is entered into the grid cell whose row and column correspond to the relevant parameter and time step respectively.

Parameters are listed to the left of the grid

Time steps are listed across the top of the grid

Values are entered into grid cells

Input grid

Copy, Edit, Configure & Share Scenarios



Run simulation

Select simulation time period

Select geographical regions to simulate

Run Simulations



Download results

Download Results



Results are available in different formats, and you can drill down by geographical region, time frame, response type, etc...

Results



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Documents

Community emergency response model (CERM)