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Utility of Ambulance Data for Real-Time Syndromic Surveillance: A Pilot in the West Midlands Region, United Kingdom

  • Dan Todkill (a1) (a2), Paul Loveridge (a3), Alex J. Elliot (a3), Roger A. Morbey (a3), Obaghe Edeghere (a2) (a3), Tracy Rayment-Bishop (a4), Chris Rayment-Bishop (a4), John E. Thornes (a5) (a6) and Gillian Smith (a3)...

The Public Health England (PHE; United Kingdom) Real-Time Syndromic Surveillance Team (ReSST) currently operates four national syndromic surveillance systems, including an emergency department system. A system based on ambulance data might provide an additional measure of the “severe” end of the clinical disease spectrum. This report describes the findings and lessons learned from the development and preliminary assessment of a pilot syndromic surveillance system using ambulance data from the West Midlands (WM) region in England.


Is an Ambulance Data Syndromic Surveillance System (ADSSS) feasible and of utility in enhancing the existing suite of PHE syndromic surveillance systems?


An ADSSS was designed, implemented, and a pilot conducted from September 1, 2015 through March 1, 2016. Surveillance cases were defined as calls to the West Midlands Ambulance Service (WMAS) regarding patients who were assigned any of 11 specified chief presenting complaints (CPCs) during the pilot period. The WMAS collected anonymized data on cases and transferred the dataset daily to ReSST, which contained anonymized information on patients’ demographics, partial postcode of patients’ location, and CPC. The 11 CPCs covered a broad range of syndromes. The dataset was analyzed descriptively each week to determine trends and key epidemiological characteristics of patients, and an automated statistical algorithm was employed daily to detect higher than expected number of calls. A preliminary assessment was undertaken to assess the feasibility, utility (including quality of key indicators), and timeliness of the system for syndromic surveillance purposes. Lessons learned and challenges were identified and recorded during the design and implementation of the system.


The pilot ADSSS collected 207,331 records of individual ambulance calls (daily mean=1,133; range=923-1,350). The ADSSS was found to be timely in detecting seasonal changes in patterns of respiratory infections and increases in case numbers during seasonal events.


Further validation is necessary; however, the findings from the assessment of the pilot ADSSS suggest that selected, but not all, ambulance indicators appear to have some utility for syndromic surveillance purposes in England. There are certain challenges that need to be addressed when designing and implementing similar systems.

Todkill D , Loveridge P , Elliot AJ , Morbey RA , Edeghere O , Rayment-Bishop T , Rayment-Bishop C , Thornes JE , Smith G . Utility of Ambulance Data for Real-Time Syndromic Surveillance: A Pilot in the West Midlands Region, United Kingdom. Prehosp Disaster Med. 2017;32(6):667672.

Corresponding author
Correspondence: Dan Todkill, MFPH Public Health England, United Kingdom E-mail:
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Conflicts of interest: none

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1. Triple, S Project. Assessment of syndromic surveillance in Europe. Lancet. 2011;378(9806):1833-1834.
2. Cooper, DL, Verlander, NQ, Elliot, AJ, et al. Can syndromic thresholds provide early warning of national influenza outbreaks? J Public Health. 2009;31(1):17-25.
3. Edge, VL, Pollari, F, Ng, LK, et al. Syndromic surveillance of Norovirus using over-the-counter sales of medications related to gastrointestinal illness. Can J Infec Dis Med Microbiol. 2006;17(4):235-241.
4. Smith, S, Smith, G, Olowokure, B, et al. Early spread of the 2009 influenza A (H1N1) pandemic in the United Kingdom--use of local syndromic data, May-August 2009. Euro Surveill. 2010;16(3):221-228.
5. Harcourt, S, Fletcher, J, Loveridge, P, et al. Developing a new syndromic surveillance system for the London 2012 Olympic and Paralympic Games. Epidemiol Infect. 2012;140(12):2152-2156.
6. Elliot, AJ, Hughes, HE, Hughes, TC, et al. Establishing an emergency department syndromic surveillance system to support the London 2012 Olympic and Paralympic Games. Emerg Med J. 2012;29(12):954-960.
7. Harcourt, S, Morbey, R, Loveridge, P, et al. Developing and validating a new national remote health advice syndromic surveillance system in England. J Public Health. 2017;39(1):184-192.
8. Greenko, J, Mostashari, F, Fine, A, et al. Clinical evaluation of the Emergency Medical Services (EMS) ambulance dispatch-based syndromic surveillance system, New York City. J Urban Health. 2003;80(1):i50-i56.
9. Harder, K, Andersen, P, Bæhr, I, et al. Electronic real-time surveillance for influenza-like illness: experience from the 2009 influenza A (H1N1) pandemic in Denmark. Euro Surveill. 2011;16(3):pii=19767.
10. Coory, M, Kelly, H, Tippett, V. Assessment of ambulance dispatch data for surveillance of influenza-like illness in Melbourne, Australia. Public Health. 2009;123(2):163-168.
11. Thornes, JE, Fisher, PA, Rayment-Bishop, T, et al. Ambulance call-outs and response times in Birmingham and the impact of extreme weather and climate change. Emerg Med J. 2014;31(3):220-228.
12. West Midlands Ambulance Service NHS Foundation Trust. Web site. Accessed May 2017.
13. Morbey, RA, Elliot, AJ, Charlett, A, et al. The application of a novel ‘rising activity, multi-level mixed effects, indicator emphasis’ (RAMMIE) method for syndromic surveillance in England. Bioinformatics. 2015;31(22):3660-3665.
14. Klaucke, DN, Buehler, JW, Thacker, SB, et al. Guidelines for evaluating surveillance systems. MMWR Morb Mortal Wkly Rep. 1988;37(Suppl 5):1-18.
15. Sears, MR, Johnston, NW. Understanding the September asthma epidemic. J Allergy Clin Immunol. 2007;120(3):526-529.
16. Mostashari, F, Fine, A, Das, D, et al. Use of ambulance dispatch data as an early warning system for communitywide influenza-like illness, New York City. J Urban Health. 2003;80(1):i43-i49.
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Prehospital and Disaster Medicine
  • ISSN: 1049-023X
  • EISSN: 1945-1938
  • URL: /core/journals/prehospital-and-disaster-medicine
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