Using syndromic surveillance to explore respiratory illness in the community

Morrison, Kirsty (2022) Using syndromic surveillance to explore respiratory illness in the community. Doctoral thesis, University of East Anglia.

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Syndromic surveillance is the “near real-time collection, analysis and interpretation” of health data. It is based on non-specific, pre-diagnostic signs and symptoms of disease, which can be used as an indicator for specific illnesses. In England, the Real-time Syndromic Surveillance Team (ReSST) operate a suit of national syndromic surveillance systems for early detection of outbreaks, situational awareness and reassurance to the lack of threat to public health.

Using several spatial and temporal statistical methods we highlight how this unique and comprehensive syndromic dataset can be used in observational epidemiological studies. In this thesis we used this data to explore demographic and socioeconomic patterns in healthcare-seeking behaviour for respiratory symptoms; estimated the community burden of healthcare presentations attributable to respiratory syncytial virus (RSV) in children; explored regional differences in the seasonality of RSV, and to explore the relationship between meteorological conditions and acute respiratory infections in children under-5 years. We utilised the frequency at which data is available, and the granularity of the local geography to explore healthcare usage in ways not previously explored. By focusing on healthcare services that provide healthcare in the community we were able to investigate a wider burden of disease than data from acute services, such as hospitalisations.

We successfully used data from syndromic surveillance in a variety of observational spatial and temporal epidemiological studies. These studies highlight that this data can provide similar observations to those from hospitalisation and laboratory data, but also provides a unique insight into healthcare-seeking behaviour in the community, which is often poorly defined. Although this data has been used successfully, this research highlights the limitations of data from syndromic surveillance. Data from syndromic surveillance has enormous potential for a variety of epidemiological research designs; however, data needs to be used within its limitations and the principles of syndromic surveillance.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Science > School of Environmental Sciences
Depositing User: Chris White
Date Deposited: 19 Aug 2022 07:51
Last Modified: 19 Aug 2022 07:51

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