17_Use_of_Web_and_Mobile_Based_Technologies_to_Solve_Organizational_and_Operational_Challenges_in_Disaster_Coordination...

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Transcript of 17_Use_of_Web_and_Mobile_Based_Technologies_to_Solve_Organizational_and_Operational_Challenges_in_Disaster_Coordination...

• Michael Smith MD, MPH• twitter: @docmikesmith skype: docmjsmith

Uses of ICT to Impact Organizational and Operational Challenges in Disaster Management

(transformational technologies)

Current uses of ICT in disasters

• Patient tracking (akin to logistics )• Assessments - epidemiologic / need / damage• Geolocating areas of need • Communications within organizations• Capturing and sharing data • Incident management

Patient tracking (logistics)

Patient tracking (logistics)

WIISARD

LA Lenert, D Kirsh, WG Griswold, C Buono, J Lyon, R Rao, TC Chan. Design and evaluation of a wireless electronic health records system for field care in mass casualty settings. J Am Med Inform Assoc. 2011;18(6):842-52. Epub 2011 Jun 27

Assessments - epidemiologic / needs / damage

Assessments - epidemiologic / needs / damage

Geolocating areas of need

Communications within organizations

Capturing and sharing data

Capturing and sharing data

Challenges to Sharing Information

• Structure and motivation of the agencies• Leadership capabilities• Social / political structures of the affected area• Needs drive communication – needs for

fundraising lead to competitive motivations

Signs of poor collaboration

• Process is confused with results • Misallocation of resources • Maldistribution of teams • Resupplies not coordinated between groups• Survivor problems evolve to a critical state

Incident management

Leading ICT challenges in disaster response

• perceiving survivors’ needs in near real-time

• assessing damage geographically

• creating greater horizontal and vertical integration of the response community

Refunite

Perceiving survivors’ needs in near real time

Perceiving survivors needs – text analysis

• Natural Language Processing - the Holy Grail• Currently uses two methods:

probalistic topic models parallel bilingual corpora

• Mechanical Turk method of crowdsourcing translations not sustainable

Probalistic topic models

Start with 2 billion tweetsTrain a binary classifier to search for all terms related to “flu” with 5,100 training examples

fever/ sneeze/ cough/ pain, etc= 1.63 million hits,

Tweets categorized as ailments, symptoms, and treatments. Excludes “confusers” – “I got Bieber fever”

QCRI’s people trained algorithm classifies large volumes of texts into various categories for individualized attention by programs like micromappers, and Crisis Trackers

Bilateral parallel corpora

Used to teach computers languagesIncludes a known language next to the other ‘slanguage’Builds similarities

(essentially the Rosetta stone in cyber age)

Providing integration – horizontal and vertical

Integration requires communication

Organization requires situational awareness