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

Dafb8db748341892bda61117ecd16a43?s=47 Ed de Quincey
November 19, 2013

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.

Dafb8db748341892bda61117ecd16a43?s=128

Ed de Quincey

November 19, 2013
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  1. 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
  2. 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
  3. 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
  4. 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
  5. 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).
  6. 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/
  7. 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.
  8. 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).
  9. 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
  10. 14.
  11. 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”
  12. 17.

    2nd GRF One Health Summit 2013 Distribution of geolocated tweets

    posted June 2012 to April 2013 containing the terms “hayfever” or “hay fever”.
  13. 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
  14. 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
  15. 20.

    2nd GRF One Health Summit 2013 #sneeze; #cantstopsneezing; #sneezing; #achoo;

    #soreeyes; #puffyeyes; #sneezy; #sniff and #sniffles Other hashtags relating to symptoms
  16. 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
  17. 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”)
  18. 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”.
  19. 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
  20. 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.
  21. 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