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Syndromic surveillance of influenza‐like illness in Scotland during the influenza A H1N1v pandemic and beyond
Author(s) -
Kavanagh Kimberley,
Robertson Chris,
Murdoch Heather,
Crooks George,
McMenamin Jim
Publication year - 2012
Publication title -
journal of the royal statistical society: series a (statistics in society)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.103
H-Index - 84
eISSN - 1467-985X
pISSN - 0964-1998
DOI - 10.1111/j.1467-985x.2012.01025.x
Subject(s) - outbreak , pandemic , public health , suite , situation awareness , medical emergency , medicine , environmental health , geography , computer science , covid-19 , infectious disease (medical specialty) , virology , disease , nursing , pathology , archaeology , aerospace engineering , engineering
Summary. Syndromic surveillance refers to the rapid monitoring of syndromic data to highlight and follow outbreaks of infectious diseases, increasing situational awareness. Such systems are based on statistical models to described routinely collected health data. We describe a working exception reporting system that is currently used in Scotland to monitor calls received by the National Health Service telephone helpline NHS24. We demonstrate the utility of the system to describe the time series data from NHS24 both at an aggregated Scotland level and at the individual health board level for two case‐studies: firstly during the initial phase of the 2009 influenza A H1N1v outbreak and secondly for the emergence of seasonal influenza in each winter season from 2006–2007 and 2010–2011. In particular, we focus on a localized cluster of infection in the Highland health board and the ability of the system to highlight this outbreak. Caveats of the system, including the effect of media reporting of the pandemic on the results and the associated statistical issues, are discussed. We discuss the adaptability and timeliness of the system and how this continues to form part of a suite of surveillance used to give early warnings to public health decision makers.