In a recent retrospective study published within the Public Health Journal, researchers evaluated the consequences of the UK’s (UK) shielding policy intervention amongst residents of Wales at 12 months.

Study: Did the UK’s public health shielding policy protect the clinically extremely vulnerable through the COVID-19 pandemic in Wales? Results of EVITE Immunity, a linked data retrospective study. Image Credit: Alonafoto/Shutterstock.com

Background

It is thought that older individuals with pre-existing comorbidities, including respiratory diseases, cardiovascular diseases, immunodeficiencies, diabetes, and malignancies, are at an increased risk of coronavirus disease 2019 (COVID-19) severity outcomes than other individuals.

In response to increasing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and deaths resulting from COVID-19, the UK government introduced a national-level intervention called ‘shielding’ to guard individuals against severe COVID-19.

Concerning the study

In the current study, researchers assessed COVID-19 testing rates and outcomes amongst shielded high-risk individuals and the unshielded public in Wales after 12 months of policy implementation.

The team retrospectively compared linked clinical and demographic data, including SARS-CoV-2 testing reports, the utilization of healthcare resources, and COVID-19-associated deaths, for EVITE Immunity study cohorts comprising individuals identified to require shielding between March 23 and May 21, 2020.

This formed the shielded cohort, and the remaining general public formed the unshielded comparator cohort. The C20 study group was formed to offer population-scale electronic health records data and facilitate the assessment of the consequences of COVID-19 in Wales.

The C20 group comprised >3.20 million Welsch individuals residing within the country on January 1, 2020, or individuals moving into or taking birth there after the date. Individuals to be shielded were tagged within the C20 group.

The team retrieved medical records concerning health events from March 23, 2020, and March 22, 2021, for comparator group individuals and from the study inclusion date as much as 12 months following policy implementation for the shielded group individuals.

The team obtained data from the secure anonymized information linkage (SAIL) databank. Data sources included the Annual District Death Extract (ADDE); the Patient Episode Database for Wales (PEDW); the Welsh Longitudinal General Practice Dataset (WLGP); COVID-19 pathology data; the Annual District Death Each day; the Consolidated Death Data; and the Critical Care Dataset.

The study outcomes included SARS-CoV-2 infection tests, positive SARS-CoV-2 infection test results, all-cause, and COVID-19-associated mortality; emergency department (ED) attendance; emergency hospitalization and hospital length of stay; intensive care unit (ICU) admissions and days in ICU; and customary mental disorder (CMD) indicators.

Generalized linear modeling was performed, and the percentages ratios (OR) and incident rate ratios (IRR) were determined, adjusting for sex and age. Deprivation was determined using the 2019 Welsh Index of Multiple Deprivation (WIMD 2019), and frailty was determined using the Electronic Frailty Index (eFI) scores, calculated on March 23, 2020.

Results

Of the 193,815 individuals initially eligible for shielding, 117,415 individuals identified through the first two phases of policy implementation, between March 23 and May 21, 2020, and linked to the C20 cohort comprised the shielded group and three,086,385 individuals comprised the comparator group.

Most people within the shielded group suffered from severe respiratory conditions (36%), immunosuppressive therapies (26%), or malignancies (19%). The shielded individuals had a greater probability of being female (54% vs.50%), aged 50.0 years or above (80% vs. 39%), residing in regions with relatively high deprivation (43% vs.41% considering upper limits), residing in care homes (0.90 vs. 0.50%), and being severely frail (58% vs. 15%) than the comparator cohort.

The share of people who underwent SARS-CoV-2 testing was greater amongst shielded individuals (OR 1.6), with lower rates of SARS-CoV-2 positivity (IRR 0.7). The speed of infections was also greater amongst shielded individuals (5.90%) than within the comparator cohort (5.70%).

As well as, shielded individuals showed a greater likelihood of death (OR 3.7), critical care hospitalization (OR 3.3), hospital emergencies (OR 2.9), emergency department (ED) attendance (OR 1.9), and CMDs (OR 1.8).

A greater proportion of shielded individuals could have undergone SARS-CoV-2 testing despite an absence of COVID-19 symptoms, e.g., to satisfy routine care hospitalization requirements or resulting from anxiety. Alternately, shielded individuals with comorbidities akin to chronic obstructive pulmonary disease (COPD) could have an increased likelihood of experiencing symptoms, increasing SARS-CoV-2 testing.

Furthermore, the supply of COVID-19 testing facilities varied geographically and across the study period. Thus, the rates of SARS-CoV-2 infection were estimated to range between 5.9% and 16% amongst shielded individuals and between 5.7% and 19% amongst non-shielded individuals.

Despite efforts to shield high-risk individuals, the vulnerable population might have been exposed to SARS-CoV-2-positive individuals at their homes, in care homes, hospitals, or other care facilities and, subsequently, be liable to COVID-19-associated complications.

The elevated rates of any-cause deaths and health resource utilization within the shielded cohort could possibly be resulting from greater illness levels amongst shielded individuals, with differences not attributed to the shielding intervention.

Conclusions

Overall, the study findings showed that mortality and the utilization of healthcare resources were greater amongst shielded individuals than most of the people, as expected for sick individuals.

Women aged ≥50.0 years, residing in highly deprived areas, and people with high frailty had an increased likelihood of being shielded. Discrepancies within the rates of COVID-19 testing, pre-existing health conditions, and deprivation were identified as potential confounders.

Nonetheless, the impact on SARS-CoV-2 infection rates couldn’t be well characterised, raising doubts regarding the success of protecting and warranting further research, including matched comparator groups, self-documented outcomes, and costs, for a radical assessment of the national health policy intervention.

Caution should be exercised before implementing the policy in future pandemics until further scientific evidence is obtainable regarding the profit, harm, and price of protecting.