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Autoregressive Integrated Moving Average (ARIMA) Modeling of Time Series of Local Telephone Triage Data for Syndromic Surveillance

Description

National telephone health advice service data have been investigated as a source for syndromic surveillance of influenza-like illness and gastroenteritis . Providing a high level of coverage, the system might serve as an early outbreak detection tool. We have previously found that telephone triage service data of acute gastroenteritis was superior to web queries as well as over-the-counter pharmacy sales of anti-diarrhea medication to detect large water- and foodborne outbreaks of gastrointestinal illness in Sweden during the years 2007–2011 (4). However, information is limited regarding the usefulness, characteristics, and signal properties of local telephone triage data for monitoring and identifying outbreaks at the community level.

Objective

Our aim was to use telephone triage data to develop a model for community-level syndromic surveillance that can detect local outbreaks of acute gastroenteritis (AGE) and influenza-like illness (ILI) and allow targeted local disease control information.

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