Abstract

Background
During COVID-19 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 between the candidates and most timely (timely and comprehensive case count) and least-biased (and most comprehensive) COVID-19 epidemic indicators from household sampling.

Findings
Laboratory tested case counts had high correlation (> 90%) with household survey incidence. Incidence and/or prevalence suggested by a self-reporting digital App, attendances to emergency departments and hospital admissions tended to highly correlate with most timely/least biased estimates (correlation generally rho > 0.70). Google search phrases, wastewater concentrations, NHS111 web visits / telephone calls and consultations with general practitioners did not highly correlate (correlation rho < 0.70).

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.
Original languageEnglish
Publication statusPublished - 15 Nov 2023

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