Potential of Social Media to determine hay fever seasons and drug efficacy

Hay fever or seasonal allergic rhinitis is a common allergic condition (Emberlin, 2010), defined as an Immunoglobulin E (IgE) mediated inflammatory response of the nasal lining following exposure to an allergen (Bousquet et al., 2008). The current UK hay fever prevalence is between 20-25% of the population, projected to rise to 39% by 2030 (Emberlin, 2010). Surges in incidence of allergic rhinitis in spring and summer are commonly know as the hay fever season.

Currently, the Meteorological Office provide weekly pollen forecasts and the Royal College of General Practitioners (RCGP) produce weekly service reports. However the former is predicative and the latter is dependent on sufferers reporting to their GP. For researchers and sufferers of hay fever, there is currently no method for identifying real-time, geolocated hay fever incidence.

A promising approach in the related field of Epidemiological Intelligence to detect seasonal illnesses is the use of Social Media (de Quincey & Kostkova, 2009). By collecting incidences of users self reporting illnesses on twitter, it has been shown that outbreaks can be predicted 1-2 weeks before RCGP data indicates (Szomszor et al, 2012). Although attempts have been made by companies such as Kimberly Clarke to take advantage of Social Media in this way, they have relied on users utilising specific, non-natural phrases within tweets and consequently have received little uptake.

This paper describes a study that has collected and analysed over 130,000, UK geolocated tweets from June 2012 to April 2013, that contained instances of the words “hayfever” and “hay fever”. Preliminary results indicate that the temporal and geographical distribution of tweets correlates with expected seasons and locations but allows for a finer level of granularity than currently available data sets. We also discuss common phrases that are being used and in particular complaints relating to drug efficacy.

Transcript

1. 2nd GRF One Health Summit 2013
   Potential of Social
   Media to determine
   hay fever seasons and
   drug efficacy
   Dr Ed de Quincey, University of Greenwich
   Dr Thomas Pantin, Blackpool Teaching Hospitals NHS
   Foundation Trust
   Photo by Maja Dumat
   

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2. 2nd GRF One Health Summit 2013
   Dr Ed de Quincey @eddequincey
   Principal Lecturer, School of Computing and Mathematical Sciences
   Head of the Web 2.0/Social Web for Learning Research Group, eCentre
   http://www2.gre.ac.uk/research/centres/ecentre/research-groups/web-2.0
   

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3. 2nd GRF One Health Summit 2013
   Hay fever or seasonal allergic rhinitis
   is a common allergic condition
   (Emberlin, 2010), defined as an
   Immunoglobulin E (IgE) mediated
   inflammatory response of the nasal
   lining following exposure to an
   allergen (Bousquet et al., 2008).
   Photo by Mislav Marohnić
   

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4. 2nd GRF One Health Summit 2013
   The current UK hay
   fever prevalence is
   between 20-25% of
   the population,
   projected to rise to
   39% by 2030
   (Emberlin, 2010).
   Photo from “Hayfever hotspots: As pollen counts rise, our
   unique British map tells you where to avoid”
   http://www.dailymail.co.uk/health/article-1015294/Hayfever-hotspots-As-
   pollen-counts-rise-unique-British-map-reveals-avoid.html
   

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5. 2nd GRF One Health Summit 2013
   Surges in incidence of allergic rhinitis in
   spring and summer are commonly
   known as the hay fever season, with
   the main pollens in the UK being birch
   pollen, March to mid May, and
   grass pollen, late May to August
   (Emberlin, 2010).
   

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6. 2nd GRF One Health Summit 2013
   The Meteorological
   Office (Met Office)
   provide weekly pollen
   forecasts and the
   Royal College of
   General
   Practitioners (RCGP)
   produce weekly
   service reports.
   http://www.metoffice.gov.uk/public/weather/forecast/
   

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7. 2nd GRF One Health Summit 2013
   Photo by “A Guy Taking Pictures”
   For researchers and sufferers of hay
   fever, there is currently no method
   for identifying real-time,
   geolocated hay fever incidence.
   

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8. 2nd GRF One Health Summit 2013
   

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9. 2nd GRF One Health Summit 2013
   500 million registered accounts
   340 million tweets per day
   

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10. 2nd GRF One Health Summit 2013
    A promising approach in the related field
    of Epidemiological Intelligence to detect
    seasonal illnesses is the use of Social Media
    (de Quincey & Kostkova, 2010). By collecting
    incidences of users self reporting illnesses
    on twitter, it has been shown that
    outbreaks can be predicted 1-2 weeks
    before RCGP data indicates (Szomszor et al, 2012).
    

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11. 2nd GRF One Health Summit 2013
    

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12. 2nd GRF One Health Summit 2013
    “1486 following, 283 followers and 134
    updates and 36 direct messages to
    hayfever sufferers on Twitter”
    http://www.figarodigital.co.uk/case-study/Kleenex.aspx
    

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13. 2nd GRF One Health Summit 2013
    http://www.socialslurp.co.uk/benadryl-pollen-hotspot-goes-tits-up/
    

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15. 2nd GRF One Health Summit 2013
    “hayfever” and “hay fever”
    

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16. 2nd GRF One Health Summit 2013
    130,233 tweets
    88,747 distinct users
    76% only posted one tweet
    Since 20th June 2012 and 2nd April 2013
    83.5% “Hayfever”
    16.5% “Hay fever”
    

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17. 2nd GRF One Health Summit 2013
    Distribution of geolocated tweets posted June 2012 to
    April 2013 containing the terms “hayfever” or “hay fever”.
    

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18. 2nd GRF One Health Summit 2013
    Distribution similar to Pollen Calendars produced by the National Pollen
    and Aerobiology Research Unit, with peaks in June/July, reductions
    through August/September, no pollen from October to January and
    then a rise in March
    

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19. 2nd GRF One Health Summit 2013
    #hayfever (6,991)
    #itchyeyes (326)
    #f@ckoff (293)
    #dying (266)
    #fml (264)
    From all tweets collected 23%
    contained hashtags
    

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20. 2nd GRF One Health Summit 2013
    #sneeze;
    #cantstopsneezing;
    #sneezing; #achoo;
    #soreeyes; #puffyeyes;
    #sneezy; #sniff and #sniffles
    Other hashtags relating to symptoms
    

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21. 2nd GRF One Health Summit 2013
    “I have hayfever” (1,006)
    “I have hay fever” (332)
    “my hayfever” (6,707)
    “my hay fever” (1,124)
    Self-reporting phrases
    

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22. 2nd GRF One Health Summit 2013
    Photo by e-Magine Art
    5,254 tweets related to
    medication were found
    (containing terms such as “medicine”; “tablets”;
    “meds”; “medication”; “pill’; “spray” and “drugs”).
    437 tweets related to
    drug efficacy
    (“tablets don’t work” and “the pills don’t work”)
    

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23. 2nd GRF One Health Summit 2013
    Only 3,924 tweets (3%) had
    a precise longitude and
    latitude.
    All tweets however
    contained an
    approximate
    location
    e.g. 16,365 were posted from
    a profile that had a location
    set as “London”.
    

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24. 2nd GRF One Health Summit 2013
    Map Source Professor Jean Emberlin, PollenUK
    

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25. 2nd GRF One Health Summit 2013
    “Thank you for sight of your map. It matches what I would
    expect to see, broadly fewer instances of pollen being
    registered in Scotland, more in the south and southeast of
    England.” - Dr Peter Burt, Biometeorologist
    

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26. 2nd GRF One Health Summit 2013
    The higher level of granularity that twitter enables for temporal analysis
    means that daily peaks of hay fever incidence can be
    identified in real time along with potentially pinpointing more
    accurate start and end dates of the seasons within
    different parts of the UK.
    

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27. 2nd GRF One Health Summit 2013
    For comparison the
    Met Office
    offered to provide
    Daily stats from
    March 2011 up until
    May 2013 for 18
    UK locations at a
    cost of £12,100 +
    Vat
    

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