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Proof of concept for a syndromic surveillance system based on routine ambulance records in the South West of England, for the influenza season 2016/2017.

Reich, T. and Budka, M., 2019. Proof of concept for a syndromic surveillance system based on routine ambulance records in the South West of England, for the influenza season 2016/2017. British Paramedic Journal, 4 (2), 22 - 30.

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Official URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC77067...

DOI: 10.29045/14784726.2019.09.4.2.22

Abstract

Introduction: The introduction of electronic patient records in the ambulance service provides new opportunities to monitor the population. Approximately 36% of patients presenting to English ambulance services are discharged at scene. Ambulance records are therefore an ideal data source for syndromic early event detection systems to monitor infectious disease in the pre-hospital population. It has been previously found that tympanic temperature records can be used to detect influenza outbreaks in emergency departments. This study aimed to determine whether routine tympanic temperature readings collected by ambulance crews can be used to detect seasonal influenza. Methods: Here we show that temperature readings do allow the detection of seasonal influenza before methods applied to conventional data sources. The counts of pyretic patients were used to calculate a sliding case ratio as a measurement to detect seasonal influenza outbreaks. This method does not rely on conventional thresholds and can be adapted to the data. Results: The data collected correlated with seasonal influenza. The 2016/2017 outbreak was detected up to nine weeks before other surveillance programmes. The results show that ambulance records can be a useful data source for biosurveillance systems. Conclusion: Temperature readings from routinely collected ambulance patient records can be used as a surveillance tool for febrile diseases.

Item Type:Article
ISSN:1478-4726
Uncontrolled Keywords:biosurveillance ; electronic patient records ; outbreak detection ; pre-hospital data
Group:Faculty of Science & Technology
ID Code:35477
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:12 May 2021 09:48
Last Modified:27 May 2021 07:53

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