Comparison of surveillance systems for monitoring COVID-19 in England: Lessons for disease surveillance

Brainard, Julii, Lake, Iain ORCID: https://orcid.org/0000-0003-4407-5357, Morbey, Roger A., Jones, Natalia ORCID: https://orcid.org/0000-0003-4025-2985, Elliot, Alex J. and Hunter, Paul ORCID: https://orcid.org/0000-0002-5608-6144 (2023) Comparison of surveillance systems for monitoring COVID-19 in England: Lessons for disease surveillance. The Lancet Public Health. ISSN 2468-2667 (In Press)

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Abstract

Background During the COVID-19 pandemic, cases were tracked using multiple surveillance systems. Some systems were completely novel and others incorporated multiple data streams to estimate case incidence and/or prevalence. How well these different surveillance systems worked as epidemic indicators is unclear. This has implications for future disease surveillance and outbreak management. Methods Data from twelve surveillance systems used to monitor the COVID-19 in England were extracted (Jan20-Nov21). These were integrated as daily time-series and comparisons undertaken using Spearman correlation between candidate alternatives and the most timely (updated daily, clinical case register) and the least-biased (from comprehensive household sampling) COVID-19 epidemic indicators, with comparisons focused on the period Sep20- Nov21. Findings Spearman statistic correlations during the full focus period between least-biased indicator (from household surveys) and other epidemic indicator time series were 0.94 (clinical cases, the most timely indicator), 0.92 (self-report case status on a digital App), 0.67 (emergency department attendances), 0.64 (NHS111 website visits), 0.63 (wastewater concentrations), 0.60 (admissions to hospital with +COVID-19 status), 0.45 (NHS111 calls), 0.08 (Google search rank for ‘covid’), -0.04 (consultations with general practitioners) and -0.37 (Google search rank for ‘coronavirus’). Time lags (-14 to +14 days) did not markedly improve these rho statistics. Clinical cases (the most timely indicator) captured a more consistent proportion of cases than the self-report digital App did. Interpretation A suite of monitoring systems is useful. The household-survey system was a most comprehensive and least-biased epidemic monitor but not very timely. Data from laboratory testing, self-reporting digital App and attendances to emergency departments were comparatively useful, fairly accurate and timely epidemic trackers.

Item Type:	Article
Uncontrolled Keywords:	surveillance,epidemic,covid-19,symptoms,health care seeking
Faculty \ School:	Faculty of Medicine and Health Sciences > Norwich Medical School Faculty of Science > School of Environmental Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA Faculty of Medicine and Health Sciences > School of Health Sciences
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Groups > Epidemiology and Public Health Faculty of Medicine and Health Sciences > Research Groups > Public Health and Health Services Research Faculty of Science > Research Groups > Environmental Social Sciences 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 Social Sciences > Research Centres > Water Security Research Centre
Depositing User:	LivePure Connector
Date Deposited:	18 Sep 2023 10:30
Last Modified:	18 Sep 2023 10:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/93052
DOI:

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