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Dynamic Network Approach to Health Surveillance. Prof. Kathleen M. Carley [email protected]. Early Warning and Disease Mapping. Understanding the general state of health in a community is critical for rapid and effective response Disaster Response Early Indicators Forecasting - PowerPoint PPT Presentation
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Center for Computational Analysis of Social and Organizational Systems
http://www.casos.cs.cmu.edu/
Dynamic Network Approach to Health Surveillance
Prof. Kathleen M. Carley
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 2
Early Warning and Disease Mapping
• Understanding the general state of health in a community is critical for rapid and effective response – Disaster Response– Early Indicators– Forecasting
• Various types of sensors are often used to provide early indications of medical conditions – water usage– OTC drug purchases
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 3
Bio-War Features
• Input– Census data – social and
organizational– School district data– Worksite and entertainment locations
& size– Hospitals and clinics locations & size– Social Network characteristics from
census– IT communication procedures &
access– Wind characteristics– Spatial layout of city– Disease models
• Influenza, small pox, anthrax, …• Illustrative Output
– Over the counter drug sales– Insurance claim reports (Dr. visits)– Emergency room reports– Absenteeism (school and work)– Web access and medical phone calls– In-house questionnaires
Agents move in networks which influence what they do, where,
with whom, and what they know, what diseases they get, when, how they respond to them, etc.Major difference in network and disease effects based on race,
gender and age.
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 4
Networks & Cyber networks
Social Network
Cyber Network
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 5
haiti.ushahidi.com
• Earthquake Jan 12, 2010• 2,471 reports posted as of
Feb 7, 2010• 6 categories of
classification– Over 25 subcategories
• Text, pictures, & video
Where do first responders start?
12 Jan 2010 photo posted to http://haiti.ushahid.com
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 6
Haiti Semantic Network (9 or more tweets)
HELP
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 7
Density Medical Categories in Ushahidi Over Time
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 8
Influenza – The “Gold” Standard
• Typical data sources– Viral Surveillance
(specimens)– Mortallity– Influenza associated
pediatric deaths– Influenza associated
hospitalization– Outpatient illness
(office/clinic visits)
http://www.cdc.gov/flu/weekly/
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 9
Google Flu Trends
http://www.google.com/publicdata
http://www.google.org/projects.html United States Flu Activity
Influenza estimate Google Flu Trends
estimate United States data
Typical data sourcesCountry provided dataSearch term based hits
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 10
News And TweetsApproximately 4-5 day lead
Copyright © 2013 CASOS, ISR, CMU – Kathleen M. Carley - Director
March 2013 11
Key Lessons
• Some medical information in social media – but inconsistent
• Key challenges – Operate at the symptom level … and many things look like
flu– Data cleaning to improve signal– Identifiers for other than flu and disaster related medical
needs– Geospatial tracking– Integration across media– Volatile state of social media
• Country specific social media technologies • Change in usage• Change in technology
• Future direction– Linking demographics and medical information– Auto-instantiation of simulation for forecasting
