Transparency and Data – UKHSA Vaccine Report

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Vaccines work. They have played a vital role in breaking the link between infection and severe outcomes and we should express our gratitude to the scientists who have developed life-saving vaccines against COVID-19 and to those who work tirelessly every day to implement the vaccination program at a pace, across the country. .

In this blog I would like to explain how we use different datasets to examine the impact of vaccination on the population.

The UK Health Safety Agency is committed to opening up the data and has been at the forefront of publishing evidence to prove the effectiveness of the UK vaccination program. We were the first to show that COVID-19 vaccines deliver high protection against the Delta variant of the virus and this data was regularly shared with policy makers and the public.

In addition to this, UKHSA publishes case, hospitalization and death rates based on vaccination status and the data in our report shows that hospitalization and death rates are substantially lower in fully vaccinated people, across all age groups. . It is therefore clear that COVID-19 vaccines provide a high level of protection against serious outcomes.

To make our data less susceptible to misinterpretation, the UK Health Safety Agency worked with the UK Statistical Authority to update some of the data tables and descriptions in the report, particularly on infection rates. in the vaccinated and unvaccinated groups. In our commitment to providing transparent and clear data, we regularly review our publications to make sure they reflect the current situation within the pandemic and will continue to work with our partners at the statistical bodies to ensure that our reports are scientifically sounder. solid as possible.

Case rates in vaccinated versus unvaccinated people

UKHSA publishes efficacy of the vaccine as a vaccine and did so for many months. This is the source that should be used to understand how effective vaccines are in the population as there is an established method to calculate it.

We publish separately the rates of COVID-19 cases, hospitalizations and deaths in vaccinated and unvaccinated groups by age. This is important for understanding the implications of the pandemic for the NHS and to help understand where to prioritize vaccination delivery.

A simple comparison of COVID-19 case rates in those who are vaccinated and unvaccinated should not be used to evaluate a vaccine’s effectiveness in preventing serious health outcomes. This is because these figures are susceptible to a number of differences between groups, in addition to the vaccine itself, and these biases mean that rates cannot be used to determine the effectiveness of vaccines.

If we look at the number of cases in vaccinated people compared to unvaccinated people, the case rate in vaccinated people appears higher for many age groups. This is because there are fundamental differences in the characteristics and behavior of vaccinated versus unvaccinated individuals. The rates therefore reflect the behavior and exposure of this population to COVID-19, not how well vaccines work. We also know that as infection rates have been high over the summer, many people have been previously infected and this has impacted the infection rate in recent weeks.

Several important factors can influence the rates of diagnosed cases of COVID-19, and this can result in a lower rate in unvaccinated people than in vaccinated ones. For instance:

  • People who are fully vaccinated may be more health conscious and therefore more likely to be tested for COVID-19 and therefore more likely to be identified as a case (based on data provided by the NHS test and trace).
  • Many of those who were at the head of the vaccination queue are those at greatest risk of COVID-19 due to their age, occupation, family circumstances, or underlying health problems.
  • People who are fully vaccinated and people who are not vaccinated may behave differently, particularly with regards to social interactions and therefore may have different levels of exposure to COVID-19.
  • People who have never been vaccinated are more likely to have contracted COVID-19 in the weeks or months leading up to the reporting period. This gives them some natural immunity to the virus for a few months which may have contributed to a lower case rate in recent weeks.

These factors are all taken into account in our published vaccine efficacy analyzes using the negative case-control approach to testing. This is a recommended method for evaluating vaccine efficacy that compares the vaccination status of people who test positive for COVID-19 with those who test negative.

This method helps to control the different propensity to undergo a test and we are able to rule out those known to have previously been infected with COVID-19. We also check for important factors including geography, time period, ethnicity, clinical risk group, living in a nursing home, and being a health or social worker.

We calculate the case rate in vaccinated people by taking the number of people who tested positive and were vaccinated and comparing it to the total number of people who were vaccinated in each age group.

The denominator

To calculate the percentage of people who have been vaccinated, we need to know how many people are eligible to receive the vaccination, this is called the denominator. While it might seem simple, there is some degree of uncertainty about the true denominator. The two most commonly used sources for deriving a denominator are:

  • The national register of the NHS (called NIMS) includes all those who have registered with the NHS and is therefore eligible to be recalled for a vaccine. While the NIMS is not perfect, it represents each unique individual who is targeted for the vaccination schedule and provides the only comparable information on the key criteria for those targeted and those who are vaccinated. One of the basic problems with NIMS is that it contains some people who have been registered with the NHS but may have moved – for example abroad – but these people have not yet been removed from the database – these are often called “ghosts”. Because vaccine uptake has been so high, even a small number of additional people included in the database will increase the number registered as unvaccinated, so this makes the rate of COVID-19 cases in some of the younger unvaccinated groups seem younger. lower than it should be.
  • The second major denominator is the National Statistical Office (ONS) which provides an estimate of the total number of people in each age group in the middle of each year. This is based on the 2011 census and updates the estimates annually using other surveys and data sources. Using this population estimate as a denominator would potentially avoid some of the “ghost” people in the younger age groups, but it would also give rise to other problems. Since ONS data is not based on a list of unique individuals, it does not allow a COVID-19 case to be linked to an individual’s vaccination status. This limits any analysis of uptake by some key criteria. In addition, current estimates appear to be underestimated in some older age groups. Since COVID-19 rates in older people are the ones we need to be most concerned about, as these age groups are at the highest risk of hospitalization and death, the use of the ONS denominator provides some inconsistent age-specific rates for these outcomes. more serious.

Neither is perfect, however for estimating case rates based on vaccination status we believe using NIMS to identify those who are vaccinated and those who are not vaccinated is the best way to provide stable and comparable data, too. if we accept that infection rates are not vaccinated, younger groups may appear to be lower than the real figure. These figures are useful for planning, for example to understand hospital workload, but should not be used to evaluate vaccine efficacy. Vaccine efficacy analysis of routine data is only possible using the variables encoded in NIMS and available individually to all people who come for a test.

What data should we look at?

Data on hospitalizations and deaths from COVID-19 are much less prone to bias, as the tests are more comprehensive and therefore it is more valid to compare rates for these severe outcomes. Even so, a properly conducted analysis is much more reliable, as explained above.

Our publication of COVID-19 vaccine surveillance data is consistent with all other vaccine surveillance data we publish, and this consistency is important for understanding the patterns we see in all of our surveillance data sources. We have consistently published data this way, aligned with other vaccine surveillance data, since the beginning of the year.

We believe that transparency, along with explanation, remains the best way to tackle disinformation. UKHSA has pledged to publish our vaccine efficacy data on a regular basis and to promptly share this evidence with others – this has played a huge role in increasing vaccine confidence in this country and around the world.

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