Assessment of ambulance dispatch data for surveillance of influenza-like illness in Melbourne, Australia.
OBJECTIVE
Ambulance dispatch data are collated electronically in many jurisdictions and have a wide reach into the community. They may therefore be useful for syndromic surveillance and early recognition of emerging infectious diseases. This study assessed whether ambulance dispatch data are suitable for influenza surveillance.


METHODS
Comparison of a time series of ambulance dispatch data from Melbourne, Australia for the years 1997-2005 with locum service and general practice (GP) sentinel surveillance data for influenza-like illness (ILI).


METHODS
All data were aggregated into 1-week periods, corresponding to the data collection period used in the GP sentinel surveillance system, which was used as the reference system. Rates of ambulance dispatches classified to respiratory or breathing problems per 1000 total dispatches were compared with rates of callouts for flu or influenza per 1000 locum calls, and rates of ILI per 1000 patients from the sentinel GPs. Signals from the ambulance data were generated using the log likelihood ratio CUSUM, a method of continuous monitoring suitable for surveillance.


RESULTS
The ambulance dispatch data displayed seasonal trends that were similar to those observed in locum service surveillance and GP sentinel systems, and identified the years with higher-than-expected seasonal ILI activity (1998 and 2003) and the epidemic year (1997). However, there was a high baseline rate of ambulance calls classified to respiratory or breathing problems (90-100 per 1000 calls) in months where there was minimal influenza activity.


CONCLUSIONS
Ambulance dispatch data have potential for syndromic surveillance, but because of the high background noise are not definitive and would need to be calibrated to suit particular local circumstances.
Coory
M D
MD
School of Population Health, University of Queensland, Mayne Medical School, Herston Road, Herston, Queensland 4006, Australia. m.coory@uq.edu.au
Kelly
H
H
Tippett
V
V
D000552:Ambulances / Q000706:statistics & numerical data*; D001315:Australia / Q000453:epidemiology; D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology*; D008390:Markov Chains; D011159:Population Surveillance / Q000379:methods*; D040442:Public Health Informatics; D012621:Seasons