Using Twitter to predict Norovirus

outbreaks

David Millsonon behalf of Callum Staff

THE PROJECT

© 2015 Food Standards Agency

Predicting and reducing Norovirus

• Tweets discussing Norovirus and its symptoms were first identified as a

proxy indicator for Norovirus cases through an MSc project

• Outbreaks are predicted using rises in tweets about Norovirus

symptoms (diarrhoea and vomiting)

• Predictions are used to inform FSA and NHS Choices interventions

• Interventions can prevent outbreaks from getting out of control by

encouraging sufferers to stay at home and avoid passing the bug on

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Citizen Need / Business Need

• Citizen Need:

• More timely surveillance = quicker reactions = more cases prevented

• Lower burden on economy and public

• Business Need:

• To understand the predictive power of social media data

• Demonstrate to Government the value of including social media

analysis in surveillance strategy

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FSA and social media analysis – from little acorns

• Cabinet Office approached the FSA to pilot a joint project with Ipsos

MORI using machine learning to categorise Tweets

• Led in producing cross-government guidance on social media research

• Set up a review and innovation group to bring the expertise of industry

and academia to Government social media research

• Designed and presented workshop on using social media in policy and

analysis

BUILDING THE MODEL

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Crowd-sourcing the keywords

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Excluding bad keywords

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Do people really tweet when they have Norovirus?

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The trade-off between usefulness and rigour

• We can rigorously predict Norovirus cases three weeks after they

happen

• To be useful to Communications, we need to predict them three weeks

before they happen

Tweets

Community cases

© 2015 Food Standards Agency

The trade-off between usefulness and rigour

• We can rigorously predict Norovirus cases three weeks after they

happen

• To be useful to Communications, we need to predict them three weeks

before they happen

Tweets

Community cases

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Calibrating the Cut Off Value

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Calibrating the Cut Off Value

0.35

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Calibrating the Cut Off Value

0.30

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Calibrating the Cut Off Value

0.25

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Calibrating the Cut Off Value

0.20

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Calibrating the Cut Off Value

0.25

USING THE RESULTS

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Outbreak predicted

Outbreak reduced (hopefully)

VALUE FOR MONEY

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Value for Money

• Cost of the project

• One analyst working approx. one day a week for 2/3 year ~ £2,500

• NHS Choices spend/external research brings total to approx. £20,000

• Cost of Norovirus

• Estimated 2.8 million cases in the UK a year at a cost of £120 million

WOULD NEED TO PREVENT JUST 500 CASES A YEAR, OR 0.02% OF

THE TOTAL, TO BE PROVIDING VALUE FOR MONEY

NEXT STEPS

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Spatial Mapping

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Summary

• A marriage of “supply” and “demand”:

• Twitter identified as a measure of Norovirus, providing information

much more rapidly than lab reports

• A need to roll out public information on Norovirus at the right time to

make the biggest impact

• A gateway project to demonstrate the value of social media analysis

• Low cost and therefore low risk, with potentially high rewards