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Morbey, Roger A., Charlett, Andre, Lake, Iain 
ORCID: https://orcid.org/0000-0003-4407-5357, Mapstone, James, Pebody, Richard, Sedgwick, James, Smith, Gillian E. and Elliot, Alex J.
(2020)
Can syndromic surveillance help forecast winter hospital bed pressures in England?
PLoS One, 15 (2).
ISSN 1932-6203
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Abstract
BACKGROUND: Health care planners need to predict demand for hospital beds to avoid deterioration in health care. Seasonal demand can be affected by respiratory illnesses which in England are monitored using syndromic surveillance systems. Therefore, we investigated the relationship between syndromic data and daily emergency hospital admissions. METHODS: We compared the timing of peaks in syndromic respiratory indicators and emergency hospital admissions, between 2013 and 2018. Furthermore, we created forecasts for daily admissions and investigated their accuracy when real-time syndromic data were included. RESULTS: We found that syndromic indicators were sensitive to changes in the timing of peaks in seasonal disease, especially influenza. However, each year, peak demand for hospital beds occurred on either 29th or 30th December, irrespective of the timing of syndromic peaks. Most forecast models using syndromic indicators explained over 70% of the seasonal variation in admissions (adjusted R square value). Forecast errors were reduced when syndromic data were included. For example, peak admissions for December 2014 and 2017 were underestimated when syndromic data were not used in models. CONCLUSION: Due to the lack of variability in the timing of the highest seasonal peak in hospital admissions, syndromic surveillance data do not provide additional early warning of timing. However, during atypical seasons syndromic data did improve the accuracy of forecast intensity.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | biochemistry, genetics and molecular biology(all),agricultural and biological sciences(all),general ,/dk/atira/pure/subjectarea/asjc/1300 |
| Faculty \ School: | Faculty of Science > School of Environmental Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA |
| UEA Research Groups: | University of East Anglia Schools > Faculty of Science > Tyndall Centre for Climate Change Research Faculty of Science > Research Centres > Tyndall Centre for Climate Change Research Faculty of Science > Research Groups > Environmental Social Sciences Faculty of Science > Research Centres > Centre for Ecology, Evolution and Conservation |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 18 Feb 2020 07:52 |
| Last Modified: | 27 Nov 2024 10:27 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/74246 |
| DOI: | 10.1371/journal.pone.0228804 |
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