New study: No evidence that shielding reduced COVID-19 infections in Wales
Shielding did not reduce COVID-19 infections in Wales: new study questions benefits of policy for vulnerable people
Peer-Reviewed PublicationA research team from Swansea University have been examining data from the year after the policy was introduced in March 2020, concluding that a “lack of clear impact on infection rates raises questions about the success of shielding.”
Shielding was introduced to protect those thought to be at highest risk of serious harm should they catch COVID-19, for example because of preconditions such as cancer or medications that they were taking. Key to protecting vulnerable people was to reduce their risk of contracting COVID-19.
The researchers examined the situation in Wales, but as shielding policy was similar across the UK, their findings will be of relevance in other countries too.
Working with the NHS, they examined how shielding affected COVID-19 infections, deaths, and admissions to hospital and intensive care. They compared the 117,000 people shielding in Wales with the rest of the population - 3 million in total – who were not.
The largest clinical categories in the shielded cohort were severe respiratory condition (35.5%), immunosuppressive therapy (25.9%) and cancer (18.6%)
The team drew on data from anonymous electronic health records routinely collected for the entire Welsh population, which are held securely within the SAIL Databank at Swansea University.
The researchers found that:
- Deaths and healthcare utilisation were higher amongst shielded people than the general population, though this would be expected as they are sicker.
- The known COVID-19 infection rate was also higher in the shielded cohort (5.9%) than in the general population (5.7%)
The researchers conclude:
“A lack of clear impact on infection rates raises questions about the success of shielding and indicates that further research is required to fully evaluate this national policy intervention.”
Commenting on the policy context the authors say:
“Shielding was an untested public health policy that was introduced in the United Kingdom early in the pandemic, in contrast to other countries where there was more focus on closing borders, lockdown, test and trace systems. The shielding policy was based on assumptions rather than evidence of effectiveness.”
Professor Helen Snooks of Swansea University Medical School, who led the research, said:
“Our study found no evidence of reduced COVID-19 infections one year after shielding was introduced. This raises questions about the benefits of shielding for vulnerable people as a policy.
Work is ongoing to compare these outcomes, as well as self-reported quality of life, with a matched group of people who were clinically vulnerable, but not selected for Shielding.
Having as much evidence as possible about the effect of policies is essential if we are to learn lessons for the future”.
The project is known as EVITE Immunity, funded through the National Core Studies Immunity Programme - commissioned by Birmingham University on behalf of UKRI; and involves collaborations with Cardiff University, Warwick University, Welsh Government and NHS Wales.
JOURNAL
Public Health
METHOD OF RESEARCH
Data/statistical analysis
SUBJECT OF RESEARCH
People
ARTICLE TITLE
Did the UK's public health shielding policy protect the clinically extremely vulnerable during the COVID-19 pandemic in Wales? Results of EVITE Immunity, a linked data retrospective study
ARTICLE PUBLICATION DATE
21-Apr-2023
Finnish population-based study: Vulnerable groups were the least likely to uptake COVID-19 vaccination
Peer-Reviewed PublicationA large-scale registry study in Finland has identified several factors associated with uptake of the first dose of COVID-19 vaccination. In particular, persons with low or no labor income and persons with mental health or substance abuse issues were less likely to vaccinate.
The study, carried out in collaboration between the University of Helsinki and the Finnish Institute of Health and Welfare, tested the association of nearly 3000 health, demographic and socio-economic variables with the uptake of the first COVID-19 vaccination dose across the entire Finnish population.
This work, just published in the Nature Human Behavior, is the largest study to date on this topic.
The single most significant factors that associated with reduced likelihood of being vaccinated were lack of labor income in the year preceding the pandemic, mother tongue other than Finnish or Swedish and having unvaccinated close relatives, especially the mother. Among health-related variables, factors related to mental health and substance abuse problems associated with reduced vaccination.
"Lack of labor income can be due to unemployment, sickness or retirement. Furthermore, among individuals with labor income, we saw that low-income earners where the least likely to vaccinate”, explains Tuomo Hartonen, Postdoctoral Researcher at the Institute for Molecular Medicine Finland FIMM, University of Helsinki.
The study was based on the FinRegistry data. Researchers analysed population-wide national health and population register data from the pre-pandemic period and compared these with the vaccination status data. The analyses were limited to people aged 30-80 years.
"A particular strength of our study is that it is based on registers covering the entire Finnish population. This way we can avoid all selection bias, which is a major challenge of survey studies", Postdoctoral Researcher Bradley Jermy from FIMM says.
The researchers stress that their results describe the association between the studied variables and vaccination uptake at the population level, but do not allow conclusions to be drawn about causal relationships. Furthermore, the generalizability of the findings outside Finland requires further studies. However, it is clear from the results that in Finland, vaccination uptake was lowest among those who are already in a vulnerable position.
Researchers created a machine learning-based model to predict vaccination uptake
In addition to studying single predictors, the research team constructed a machine learning-based model to predict vaccination uptake. This prediction model allowed the researchers to group individuals according to their likelihood of receiving the COVID-19 vaccine.
Approximately 90% of the total study population received at least one dose of COVID-19 vaccination. In contrast, the group with the lowest probability of being vaccinated based on the model had a vaccination rate of less than 19%.
“Our research has created a framework for using machine learning and statistical approaches to identify those groups that are at higher risk of not vaccinating”, says the corresponding author of the study, Associate Professor Andrea Ganna from FIMM.
“These results and the predictive model could be used in the future, for example in designing vaccination campaigns”, says the Principal Investigator of the FinRegistry study, Research Professor Markus Perola from THL.
“This study is a great example of the possibilities that the FinRegistry study creates for investigating highly topical issues in a short timeframe. The collaboration between THL's genetic and registry researchers and FIMM scientists will help to understand the many pathways that lead to susceptibility to different diseases," Perola continues.
The study is part of the FinRegistry project, a joint research project between the Finnish Institute for Health and Welfare (THL) and the Institute for Molecular Medicine Finland (FIMM) at the University of Helsinki.
JOURNAL
Nature Human Behaviour
ARTICLE TITLE
Nationwide health, socio-economic and genetic predictors of COVID-19 vaccination status in Finland
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