Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Dec 5, 2024
Date Accepted: Sep 1, 2025
Comparison of Virus Watch COVID-19 positivity, incidence and hospitalisation rates with other surveillance systems: Surveillance Study
ABSTRACT
Background:
Effective disease surveillance is essential for understanding epidemiology, detecting outbreaks, and enabling timely public health responses, as demonstrated during the COVID-19 pandemic. In the UK, large-scale studies such as the ONS COVID-19 Infection Survey (CIS) monitored SARS-CoV-2 transmission but required significant resources, making them challenging to sustain in resource-limited settings. In contrast, the Virus Watch study, with a lower cost, relied on self-reported data and symptomatic testing, while SARI Watch leveraged hospital data for cost-effective surveillance.
Objective:
Our study evaluates Virus Watch’s effectiveness in tracking COVID-19 trends, using ONS CIS and SARI Watch as benchmarks for comparison.
Methods:
We used the Virus Watch prospective community cohort study to estimate COVID-19 positivity, incidence and hospitalisation rates in England and Wales from June 2020 to February 2023. We compared our findings with modelled positivity and incidence rates from ONS CIS and COVID-19 hospitalisation rates from SARI Watch using 9-week rolling Spearman’s ⍴ correlation to measure synchrony.
Results:
58,628 participants were recruited into the Virus Watch study between June 2020 and March 2022, of whom 52,526 (90%) were reported to be living in England and 1,532 (2.6%) in Wales. Virus Watch estimates of COVID-19 positivity and incidence rates in England and Wales were highly correlated with those from ONS CIS. Despite lower absolute values in Virus Watch estimates, both studies showed strong global (overall ⍴s > 0.90) and local (median ⍴s > 0.75) synchrony over time. However, Virus Watch estimates of hospitalisations with COVID-19 were significantly lower and less synchronised with SARI Watch estimates (overall: 0.72, P<.001; median: 0.49, IQR 0.15-0.70). In Wales, Virus Watch estimates exhibited greater variability and lower local synchrony compared to England (overall positivity ⍴: 0.75, P<.001; overall incidence rate ⍴: 0.85, P<.001).
Conclusions:
Our results highlight the effectiveness of the Virus Watch approach in providing accurate estimates of COVID-19 positivity and incidence rates, even in the absence of national surveillance systems. This low-cost method can be adapted to various settings, particularly low-resource ones, to strengthen public health surveillance and inform timely interventions.
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