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Ascertainment and Enhancement of Gastrointestinal Disease Surveillance and Statistics (AEGISS)

Project Code: B08006

31/03/2004

Health Protection Agency
Hawtin, P ; Turner, A;
University of Southampton
Bryant, T;
Lancaster University
Diggle, P

Project AEGISS set out to develop spatio-temporal statistical modelling for the surveillance of gastrointestinal disease and establish the datastreams required to support the application of the statistical analysis. New methods of case ascertainment for Primary Care and Microbiology laboratories were to be developed to reduce the time to detection of emerging outbreaks and to further interpret the statistical anomalous findings. Geographical Information Systems were recruited and developed to enable the real-time online interrogation of the datastreams and to effectively manage the different outputs, including environmental and demographic, to present a complete epidemiological picture. The project’s overall purpose was to decrease time to detection, which should allow earlier intervention. This, in turn, would reduce the burden of gastrointestinal disease within the community. This system should also facilitate the detection of non-infectious events and possible point source multi-pathogen outbreaks. Moreover, this system would be applicable to other syndromic surveillance.

Preliminary work found that faecal sampling between GPs and practices to be highly variable, both in the timing of sampling in the course of symptoms and in patient type. It is also known that only a small minority of patient presenting with acute gastrointestinal symptoms are sampled at all. Alternative sources of medical advice are now available, e.g. NHSDirect, suggesting that there may be a decrease in the availability of samples for microbiological analysis. As current surveillance is largely based on the positive results of faecal microbiology, it is rendered insensitive by sampling practices and selective microbiological protocols.

Initially, a paper proforma, to be optically scanned, was designed in conjunction with representatives from Primary Care for the ascertainment of a minimum dataset on each patient presenting with acute onset of gastrointestinal disease. This was successfully piloted together with a self-administered risk factor questionnaire. Electronic reporting was also introduced as a pilot scheme into several practices. The level of consistent reporting by individual GPs and at practice level was not achieved sufficiently to develop the spatio-temporal statistical analysis and so a NHSDirect datastream was established. Differences were detected in the patient age profile between cases presenting to GP Practices and NHSDirect and the minimum dataset was not all available from NHSDirect data. Furthermore, the NHSDirect was relatively sparse compared to the estimated numbers expected from Primary Care. However, this data source did enable the development of a statistical model from which examples of anomalous locations could be identified. Microbiological results were then scrutinised for that location and time for pathogen isolation/identification trends. Although these post hoc comparisons have no direct link, their temporal association and, in some of the examples, patient demographic similarities and changes in trend, suggest that the model may be identifying locations where significant microbiological events are later detected. The model would need to be further evaluated using GP derived data but, if proven, has the potential for identifying locations for enhanced surveillance. It may be possible to characterise the cases in the statistical anomalous location sufficiently enough to generate a prospective case definition with which the GPs in that area could be alerted. Under this protocol case ascertainment, structured sampling and risk factor exposure could be monitored prospectively and intervention instigated as early as possible.

Full exploitation of the interactive website has yet to be achieved. For example, the download of Salmonella Reference Laboratory results was not established. There is great potential in this approach for the reduction of double data entry in surveillance and the promotion of cross boundary and cross professional working.

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