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1.
Public Health ; 232: 114-120, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38772199

ABSTRACT

OBJECTIVE: To set up and evaluate a new surveillance system for severe acute respiratory infection (SARI) in Scotland. STUDY DESIGN: Cross-sectional study and evaluation of surveillance system. METHODS: The SARI case definition comprised patients aged 16 years or over with an acute respiratory illness presentation requiring testing for influenza and SARS-CoV-2 and hospital admission. Data were collected from SARI cases by research nurses in one tertiary teaching hospital using a bespoke data collection tool from November 2021 to May 2022. Descriptive analyses of SARI cases were carried out. The following attributes of the surveillance system were evaluated according to Centers for Disease Control and Prevention (CDC) guidelines: stability, data quality, timeliness, positive predictive value, representativeness, simplicity, acceptability and flexibility. RESULTS: The final surveillance dataset comprised 1163 records, with cases peaking in ISO week 50 (week ending 19/12/2021). The system produced a stable stream of surveillance data, with the proportion of SARI records with sufficient information for effective surveillance increasing from 65.4% during the first month to 87.0% over time. Similarly, the proportion where data collection was completed promptly was low initially, but increased to 50%-65% during later periods. CONCLUSION: SARI surveillance was successfully established in one hospital, but for a national system, additional sentinel hospital sites across Scotland, with flexibility to ensure consistently high data completeness and timeliness are needed. Data collection should be automated where possible, and demands on clinicians minimised. SARI surveillance should be embedded and resourced as part of a national respiratory surveillance strategy.


Subject(s)
COVID-19 , Tertiary Care Centers , Humans , Scotland/epidemiology , Cross-Sectional Studies , Female , COVID-19/epidemiology , Male , Adult , Middle Aged , Aged , Adolescent , Respiratory Tract Infections/epidemiology , Respiratory Tract Infections/diagnosis , SARS-CoV-2 , Young Adult , Influenza, Human/epidemiology , Influenza, Human/diagnosis , Population Surveillance/methods
2.
Public Health ; 213: 5-11, 2022 Dec.
Article in English | MEDLINE | ID: mdl-36306639

ABSTRACT

OBJECTIVES: The COVID-19 pandemic highlighted the importance of routine syndromic surveillance of respiratory infections, specifically new cases of severe acute respiratory infection (SARI). This surveillance often relies on questionnaires carried out by research nurses or transcriptions of doctor's notes, but existing, routinely collected electronic healthcare data sets are increasingly being used for such surveillance. We investigated how patient diagnosis codes, recorded within such data sets, could be used to capture SARI trends in Scotland. STUDY DESIGN: We conducted a retrospective observational study using electronic healthcare data sets between 2017 and 2022. METHODS: Sensitive, specific and timely case definition (CDs) based on patient diagnosis codes contained within national registers in Scotland were proposed to identify SARI cases. Representativeness and sensitivity analyses were performed to assess how well SARI cases captured by each definition matched trends in historic influenza and SARS-CoV-2 data. RESULTS: All CDs accurately captured the peaks seen in laboratory-confirmed positive influenza and SARS-CoV-2 data, although the completeness of patient diagnosis records was discovered to vary widely. The timely CD provided the earliest detection of changes in SARI activity, whilst the sensitive CD provided insight into the burden and severity of SARI infections. CONCLUSIONS: A universal SARI surveillance system has been developed and demonstrated to accurately capture seasonal SARI trends. It can be used as an indicator of emerging secondary care burden of emerging SARI outbreaks. The system further strengthens Scotland's existing strategies for respiratory surveillance, and the methods described here can be applied within any country with suitable electronic patient records.


Subject(s)
COVID-19 , Influenza, Human , Humans , Influenza, Human/diagnosis , Influenza, Human/epidemiology , SARS-CoV-2 , COVID-19/epidemiology , Pandemics , Hospitals
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