  Following the UK Government's Living with COVID-19 Strategy and the end of
universal testing, hospital admissions are an increasingly important measure of
COVID-19 pandemic pressure. Understanding leading indicators of admissions at
National Health Service (NHS) Trust, regional and national geographies help
health services plan capacity needs and prepare for ongoing pressures. We
explored the spatio-temporal relationships of leading indicators of hospital
pressure across successive waves of SARS-CoV-2 incidence in England. This
includes an analysis of internet search volume values from Google Trends, NHS
triage calls and online queries, the NHS COVID-19 App, lateral flow devices and
the ZOE App. Data sources were analysed for their feasibility as leading
indicators using linear and non-linear methods; granger causality, cross
correlations and dynamic time warping at fine spatial scales. Consistent
temporal and spatial relationships were found for some of the leading
indicators assessed across resurgent waves of COVID-19. Google Trends and NHS
queries consistently led admissions in over 70% of Trusts, with lead times
ranging from 5-20 days, whereas an inconsistent relationship was found for the
ZOE app, NHS COVID-19 App, and rapid testing, that diminished with granularity,
showing limited autocorrelation of leads between -7 to 7 days. This work shows
that novel syndromic surveillance data has utility for understanding the
expected hospital burden at fine spatial scales. The analysis shows at low
level geographies that some surveillance sources can predict hospital
admissions, though care must be taken in relying on the lead times and
consistency between waves.
