(C-057) Impact of cumulative non-pharmacological interventions on the incidence of acute and chronic conditions before and after the COVID-19 pandemic in Europe and the United States

Background: The COVID-19 pandemic profoundly affected healthcare worldwide through direct viral impacts and indirect effects of non-pharmacological interventions (NPIs). Data on cumulative NPI effects on health remain scarce.

Objectives: This study aims to examine the association between cumulative NPIs, measured by the Area Under the Curve (AUC) of country-specific Stringency Index (SI) and the occurrence of numerous health outcomes: selected acute and chronic conditions, health utilisation and post-acute COVIV-19 related complications.

Methods: We used data from seven international health databases standardised to the Observational Medical Outcomes Partnership (OMOP) common data model: UK CPRD GOLD; THIN UK, Spain, Belgium, Romania and France; and US Pharmetrics Plus. We calculated incidence rates for all outcomes of interest and performed time series analysis to assess changes pre-, during, and post- national lockdowns. We also studied the association between the AUC of the SI and incidence rates for each outcome and country, with linear and distributed lag models.

Results: A ubiquitous decline in rates was observed across most conditions during the first lockdown. Recovery varied, with countries implementing a second lockdown, like the UK, experiencing a slower return to baseline levels. This delay was particularly notable for conditions diagnosed in primary care or through population-level screening: asthma, hypertension, breast and colorectal cancer. Post-acute COVID-19-related symptoms demonstrated a clear relationship with COVID-19 infection rates, while more severe complications, including thromboembolic and cardiac events, showed a marked increase in post-pandemic incidence. The association of the AUC of SI was particularly strong for the primary care diagnosed and routinely screened health outcomes but heterogeneous across countries for other conditions, showing the complexity of NPIs effects on healthcare services. Lag effects were not very pronounced, being immediate consequences of the NPIs the most impactful.Results for the incidence rates, time series and AUC modelling can be found at:
https://dpa-pde-oxford.shinyapps.io/CHAPTER_Oxf/
https://dpa-pde-oxford.shinyapps.io/CHAPTER_Oxf_AUC/

Conclusions: Our findings highlight the pronounced effect of lockdowns on conditions routinely diagnosed or screened at the population level and contribute to the growing research on healthcare resilience and the need for greater preparedness to minimise health consequences of future pandemics.