Dynamic Network Approach to Health Surveillance

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Dynamic Network Approach to Health Surveillance. Prof. Kathleen M. Carley kathleen.carley@cs.cmu.edu. 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

kathleen.carley@cs.cmu.edu

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

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