Communicating the detection capabilities of syndromic surveillance systems

Increasingly public health decision-makers are using syndromic surveillance for real-time reassurance and situational awareness in addition to early warning1. Decision-makers using intelligence, including syndromic data, need to understand what the systems are capable of detecting, what they cannot detect and specifically how much reassurance should be inferred when syndromic systems report nothing detected. In this study we quantify the detection capabilities of syndromic surveillance systems used by Public Health England (PHE).

June 18, 2019

Comparison of statistical algorithms for syndromic surveillance aberration detection

Syndromic surveillance involves monitoring big health datasets to provide early warning of threats to public health. Public health authorities use statistical detection algorithms to interrogate these datasets for aberrations that are indicative of emerging threats. The algorithm currently in use at Public Health England (PHE) for syndromic surveillance is the ‘rising activity, multi-level mixed effects, indicator emphasis’ (RAMMIE) method (Morbey et al, 2015), which fits a mixed model to counts of syndromes on a daily basis.

January 21, 2018

Updating syndromic surveillance baselines following public health interventions

Public Health England's syndromic surveillance service monitor presentations for gastrointestinal illness to detect increases in health care seeking behaviour driven by infectious gastrointestinal disease. We use regression models to create baselines for expected activity and then identify any periods of signficant increases. The introduction of a rotavirus vaccine in England during July 2013 (Bawa, Z. et al. 2015) led to a reduction in incidence of the disease, requiring a readjustment of baselines.

Objective:

January 21, 2018

Using real-time syndromic surveillance to monitor the health effects of air pollution

The negative effect of air pollution on human health is well documented illustrating increased risk of respiratory, cardiac and other health conditions. Currently, during air pollution episodes Public Health England (PHE) syndromic surveillance systems provide a near real-time analysis of the health impact of poor air quality.

January 21, 2018

Infant fever trends following the launch of the meningococcal B vaccine in the UK

From 1 September 2015, babies in the United Kingdom (UK) born on/after 1 July 2015 became eligible to receive the MenB vaccine, given at 2 and 4 months of age, with a booster at 12 months. Early trials found a high prevalence of fever (over 38°C) in babies given the vaccine with other routine vaccines at 2 and 4 months. We used syndromic surveillance data to assess whether there had been increased family doctor (general practitioner (GP)) consultations for fever in young infants following the introduction of the vaccine. 

Objective

July 06, 2017

Interpreting specific and general respiratory indicators in syndromic surveillance

Public Health England (PHE) uses syndromic surveillance systems to monitor for seasonal increases in respiratory illness. Respiratory illnesses create a considerable burden on health care services and therefore identifying the timing and intensity of peaks of activity is important for public health decision-making. Furthermore, identifying the incidence of specific respiratory pathogens circulating in the community is essential for targeting public health interventions e.g. vaccination.

July 10, 2017

“That was then, this is now” improving public health syndromic surveillance baselines

Syndromic surveillance systems are used by Public Health England (PHE) to detect changes in health care activity that are indicative of potential threats to public health. By providing early warning and situational awareness, these systems play a key role in supporting infectious disease surveillance programmes, decision making and supporting public health interventions. In order to improve the identification of unusual activity, we created new baselines to model seasonally expected activity in the absence of outbreaks or other incidents.

August 20, 2017

The importance of age-specific data in routine syndromic surveillance

When monitoring public health incidents using syndromic surveillance systems, Public Health England (PHE) uses the age of the presenting patient as a key indicator to further assess the severity, impact of the incident, and to provide intelligence on the likely cause. However the age distribution of cases is usually not considered until after unusual activity has been identified in the allages population data. We assessed whether monitoring specific age groups contemporaneously could improve the timeliness, specificity and sensitivity of public health surveillance.

August 20, 2017

Beyond aberration detection, coping with multiple exceedances in a national syndromic surveillance service

Public Health England uses data from four national syndromic surveillance systems to support public health programmes and identify unusual activity. Each system monitors a wide range of respiratory, gastrointestinal and other syndromes at a local, regional and national level. As a result, over 12,000 ‘signals’ (combining syndrome and geography) need to be assessed each day to identify aberrations. In this webinar I will describe how the ‘big data’ collected daily are translated into useful information for public health surveillance.

March 15, 2017

Ensuring the Week Goes Smoothly - Improving Daily Surveillance Visualization

Real-time syndromic surveillance requires daily surveillance of a range of health data sources. Most real-time data sources from health care systems exhibit large day of the week fluctuations as service provision and patient behaviour varies by day of the week. Regular day of the week effects are further complicated by the occurrence of public holidays (usually 8 per year in England), which can limit the availability of certain services and affect patient behaviour.

August 29, 2017

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