Twitter in the age of pandemics: Infodemiology and Infoveillance

Gunther Eysenbach MD MPH

Gunther Eysenbach MD MPHDirector, Consumer Health & Public Health Informatics Lab

Associate Professor Department of Health Policy, Management and Evaluation, University of Toronto;

Senior Scientist, Centre for Global eHealth Innovation,Division of Medical Decision Making and Health Care Research; Toronto General Research Institute of the UHN, Toronto General Hospital, Canada

[email protected]

Pandemics in the Age of Twitter: A Case Study of Infodemiology and Infoveillance as New Methods for Knowledge Translation Research and Syndromic Surveillance

Medicine 2.0MaastrichtNov 2010

http://sickcity.org/

Economists have something public health practitioners don’t have: Real-time indices to track behavior and emotions

The premise

“The Internet has made measurable what was previously immeasurable: The

distribution of health information in a population, tracking (in real time) health

information trends over time, and identifying gaps between information

supply and demand. “

Eysenbach G. Infodemiology. Proc AMIA Fall Symp 2006

Research Goals

Developing innovative tools & methods to measure/track health-related attitudes, knowledge, emotions, public attention, behavior in real time for public healthusing textual data from the Internet & Social Media

Investigate how the public is using social media during a pandemic, and how social media can be used to engage the public

Gunther Eysenbach MD, MPH, www.medicine20congress.comImage Source:

http://web2.wsj2.com/

Studying information patterns in the era of user-generated information (Web 2.0) enables us to measure user attitudes, behavior, awareness, knowledge, attention, information needs etc.

Infoveillance

• Predicting/tracking outbreaks and other public-health relevant events,

• Tracking changes in behavior, attitudes, knowledge (e.g. as a result of public health messages or interventions)

• Situational awareness regarding current concerns, issues, questions, emotions, of the public

Eysenbach G. Infodemiology and InfoveillanceJ Med Internet Res 2009: e11

http://www.jmir.org/2009/1/e11

The science of distribution and determinants of disease in populations

Epidemiology,Polls, Focus groups

Public Health ProfessionalsPolicy Makers

Public Health InterventionsPolicy Decisions

Population Behaviour, Attitudes, Health Status

Traditional Knowledge Translation Circle

PR / Media Campaigns






Information &Communicationpatterns

Web 1.0: Webpages, News

Web 2.0: User generated content, social media

Searches, Navigation, Clicks



“Infodemiology”the epidemiology of information

Analyzing information & communication patterns (on the web)






Information &Communicationpatterns

Web 1.0: Webpages, News

Web 2.0: User generated content, social media

Searches, Navigation, Clicks



Infoveillance

Metrics

InfovigilAggregator/Datamining/Vizualisation

InfovigilVision: an open source infoveillance prototype

Centre for Global eHealth Innovation, Toronto

Public,Clinicians,Epidemiologists

Websites

FilterKeywords / Concepts of Interest

OnlineQuestionnaires

Swine Flu / H1N1 Tweets Analytics Project

• between May 1st, 2009 and April 1st, 2010, we archived over 3 million tweets containing the keywords or hashtags (#) “H1N1”, “swine flu”, and “swineflu”.

• Also archived content of cited URLs using webcitation.org

What are people talking about in tweets?

Qualitative analysis of H1N1/Swine Flu tweets

23 %

53 %

14 %

8 %

1 %

2 %

Chew C, Eysenbach G. Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak. PLoS ONE, 2009 November 29th;5(11): e14118. http://dx.plos.org/10.1371/journal.pone.0014118.

http://dx.plos.org/10.1371/journal.pone.0014118





Absolute number of tweets(Blue: swine flu, red: h1n1)

spikes mainly due to major news events e.g • [A] WHO declares pandemic, • [P] Obama declares national emergency• [B] Harry Potter actor Rupert Grint has Swine Flu

Media Resonance Analysis

Relative usage of “H1N1” terminology over “Swine Flu”H1N1:SwineFlu Ratio

• The relative proportion of tweets using “H1N1” increased from 8.8% to 40.5% in an almost linear fashion (R2= .788; p < .001), indicating a gradual adoption of the WHO-recommended H1N1 terminology as opposed to “Swine Flu”

• also social media campaigns show some effect ([G] #oink campaign of farmers)

“Happiness / Humor / Mood Index”:Smileys : Frowneys Ratio

Question IndexNumber of tweets with ? : Total Tweets

Prayer IndexNumber of tweets with “pray” : Total Tweets

H1N1 Hospitalizations / Deaths

Personal Experiences







Number of tweets with “personal experiences” correlates to H1N1 incidence

Chew & Eysenbach. Pandemics in the Age of Twitter: Content Analysis of Tweets during the 2009 H1N1 Outbreak. PloS One 2010 (in press)

Vaccine / Vaccination Mentionings







Sentiment AnalysisH1N1 Vaccine Sentiment over Time

10

20

30

40

50

60

18-May-09 15-Jun-09 13-Jul-09 10-Aug-09 7-Sep-09 5-Oct-09 2-Nov-09 30-Nov-09 28-Dec-09

% of Sample

ANTI

PRO

negative emotion3%

paranoia/distrust

physiological safety/harm/harm to

children24%

vaccine and pandemic downplay/dissuasion

16%

dissatisfaction roll-out

negative intention5%

Anti-Vaccination Themes

Qualitative content analysis of n=689 anti-vaccination tweets

18 May - 28 Dec 2009

Conclusions• Infoveillance: New methodology, offers wealth of

quantitative + qualitative data, complementary to traditional survey methods, more timely and inexpensive

• Twitter is a rich source of opinions and experiences, which can be used for near real-time content and sentiment analysis, knowledge translation research, and potentially as a syndromic surveillance tool, allowing health authorities to become aware of and respond to real or perceived concerns/issues raised by the public

• Social media appeared underused by Canadian public health authorities during the H1N1 pandemic

“In the era of the 24-hour news cycle, the traditional once-a-day press conference

featuring talking heads with a bunch of fancy titles has to be revamped and supplemented

with Twitter posts, YouTube videos and the like.

The public needs to be engaged in conversations and debate about issues of public

health, they don’t need to be lectured to.”-Andre Picard

Picard A (2010) Lessons of H1N1: Preach less, reveal more. Globe and Mail. Available: http://www.webcitation.org/5qYZly99e.

http://www.webcitation.org/5qYZly99e



Principal Investigator:Gunther Eysenbach MD MPH

Director, Consumer Health & Public Health Informatics LabCentre for Global eHealth Innovation

[email protected]

• Thanks to CIHR & Reviewers

• Cynthia Chew (MSc Student): Coding & Qualitative Analysis of Tweets

• Latifa Mnyusiwalla (MHI Student): Vaccination Sentiment Analysis

• Marina Sokolova PhD, CHEO Ottawa: Natural Language Processing

• Phil Cairns: Developer

Acknowledgements

Health & Medicine

Twitter in the age of pandemics: Infodemiology and Infoveillance