ict for disaster resilience bern shen md cdc/pihoa workshop honolulu, 5 feb 2013
TRANSCRIPT
ICT for Disaster Resilience
Bern Shen MDCDC/PIHOA workshopHonolulu, 5 Feb 2013
• Problem statement & solution hypothesis• Enabling technology trends • Use cases• Legal, policy & implementation issues
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• Properties of resilience– Robustness– Redundancy– Resourcefulness– Rapidity
• Dimensions of resilience– Technical– Organizational– Social– Economic
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Problem statement & solution hypothesis
“In an emergency, you must treat information as a commodity as important as the more
traditional and tangible commodities like food, water, and shelter.”
Jane Holl Lute, Deputy Secretary, Homeland Security (Lesperance, et. al, 2010:3)
Enabling tech trends
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‘92 ‘97 ‘02 ‘07 ‘12 ‘17
First text msg sent
First commercial SMS service
Twitter founded, Facebook opens to general public
US mobile subscribers send & receive more texts than voice calls
More than half of US owns smart phones; 60,000+ health apps
Global SMS traffic, 1012
Global mobile subscriptions, 109
Use cases
• 2009 flu pandemic – Twitter, texting, YouTube• 2010 Haiti earthquake – Ushahidi, Facebook• 2010 Deepwater oil spill – texting• Others…
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“We've seen now… from wildfires in California and Boulder to the recent ice storm and snowstorms...the public is putting out better situation awareness than many of our own agencies can with our official datasets.”
- Craig Fugate, FEMA Administrator, 2011
ICT/social media levels of use
• Monitor• Command/control• Coordinate• Cooperate• Collaborate
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Prevention
Surveillance & detection
Analysis
ResponseRemediation &
recovery
Sample text messages
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Intelligent messaging
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A handful of generic & passive messagesYou should <do
this pretty boring thing> because we said so.
You should <do this pretty boring thing> because we said so.
Status Quo
Yawn. No response.Yawn. No response.
Volumes of inspired, actionable, evidence-based messages created & refreshed continuously
Guilty Message
Gain-frameMessage
Emoticon:-) Message
Message Optimization
Communications Map
CrowdsourcingLifecycle Management
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txt1 txt2
txt4 txt3
Dynamic messaging based on how different people respond to different messages over time using heuristic & predictive models
Multidimensional heat map connecting message type, business rules & performance metrics visualizes data effectively
APIs allowing content writers across the demographic spectrum to infuse the system with fresh messages using strict guidelines
Natural program, patient & seasonal cycles are considered by the analytics to refresh messaging and maintain engagement rate
Legal, policy & implementation issues
• Data privacy & security• Resources• Infrastructure• Social/cultural change• Other…
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Let’s do this.