Background The introduction of electronic patient records in the ambulance service allows to use these to monitor the population. Most patients are discharged at scene therefore this data represents a new source for syndromic disease surveillance. The accessibility and extent of the records allows to apply early event detection (EED) systems to monitor the prehospital population. Here such a system is applied to tympanic temperature readings to detect seasonal influenza.
Method Tympanic temperature readings, are recorded for all patients and were used to determine daily and weekly numbers of pyretic patients. A method adapted from Singh et al. (2016) based on case ratios (CR) was used to detect the start of the seasonal influenza outbreak. This method does not rely on thresholds, and was applied in a sliding manor as EED system.
Results The data represented annually 15.96% of the population, focused on the elderly. It matched the progress of seasonal influenza cases from sentinel surveillance programs. For the season 2016/17 an increase in cases was detected with an estimated specificity and sensitivity of 99.7% and 100%, up to 9 weeks before sentinel surveillance programs. Furthermore, an unanticipated outbreak of Escherichia coli was detected.
Conclusion It was shown, disease outbreaks can be monitored using prehospital tympanic temperature data. Thus, making the ambulance service an ideal source for syndromic surveillance. The method used was effective and can be easily deployed to monitor specific syndromes to distinguish between infectious agents. The method is easily adapted to sample rates and noisiness of the data to prevent false alarms.
Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.