Vaccines work. You have played a vital role in breaking the link between infections and serious consequences, and we should thank the scientists who developed life-saving vaccines for COVID-19 and those who work tirelessly every day to contribute to the vaccine program. introduce pace across the country.
In this blog I want to explain how we use different sets of data to study the effects of vaccination on the population.
The UK Health Authority is committed to data openness and has been at the forefront of releasing evidence to show the effectiveness of the UK vaccination program. We were the first to show that COVID-19 vaccines offer high protection against that Delta variant of the virus and this data has been regularly shared with policy makers and the public.
In addition, the UKHSA publishes case, hospital and death rates by vaccination status, and the data in our report shows that hospitalization and death rates are significantly lower for fully vaccinated people across all age groups. It is therefore clear that COVID-19 vaccines offer a high level of protection from serious consequences.
To make our data less prone to misinterpretation, the UK Health and Safety Authority worked with the UK Statistics Service to update some of the data tables and descriptions in the report, particularly on infection rates in vaccinated and unvaccinated groups. In our commitment to transparent and clear data, we regularly review our publications to ensure that they reflect the current situation within the pandemic and will continue to work with our partners in the statistical authorities to ensure that our reporting is as scientifically sound as possible .
Number of cases in vaccinated versus unvaccinated people
UKHSA released Effectiveness of the vaccine by vaccine and that 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 of calculation.
We publish the rates of COVID-19 cases, hospitalizations and deaths in vaccinated and unvaccinated groups separated by age. This is important to understand the impact of the pandemic on the NHS and where vaccination should be prioritized.
A simple comparison of COVID-19 case rates in vaccinated and unvaccinated people should not be used to assess how effective a vaccine is in preventing serious health outcomes. This is because these numbers are prone to a number of differences between the groups, aside from the vaccine itself, and these biases mean you can’t use the rates to determine how well the vaccines are working.
If one looks at the number of cases in vaccinated persons compared to unvaccinated persons, the case rate for vaccinated persons appears to be higher for many age groups. This is because there are significant differences in the characteristics and behavior of people who are vaccinated compared to those who have not been vaccinated. The rates therefore reflect the behavior and exposure of this population to COVID-19, not the effectiveness of the vaccines. We also know that due to the high infection rates in the summer, many people were previously infected, which has had an impact on the infection rate in recent weeks.
Several important factors can affect the rate of diagnosed COVID-19 cases, and this may result in a lower rate in unvaccinated than vaccinated people. For example:
- Individuals 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 NHS Test and Trace).
- Many of those who have been at the top of the queue for vaccination are at higher risk for COVID-19 because of their age, occupation, family circumstances, or underlying health issues.
- People who are fully vaccinated and people who are not vaccinated can behave differently, especially with regard to social interactions, and therefore be infected with COVID-19 to different degrees.
- People who have never been vaccinated are more likely to contract COVID-19 in the weeks or months prior 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 included in our published vaccine efficacy analyzes which use the negative case control approach. This is a recommended method of evaluating vaccine effectiveness, comparing 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 have a test and we are able to exclude those who are known to have been previously infected with COVID-19. We also control important factors such as geography, time period, ethnicity, clinical risk group, life in a nursing home and work as a health or social worker.
We calculate the case rate in vaccinated people by comparing the number of people who tested positive and vaccinated with the total number of people vaccinated in each age group.
To calculate the percentage of people vaccinated, we need to know how many people can get the vaccination, this is called the denominator. While it may seem simple, there is some uncertainty about the true denominator. The two sources most commonly used to derive a denominator are:
- The national NHS registry (called NIMS) includes everyone who has registered with the NHS and is therefore eligible to be called for a vaccine. While not perfect, NIMS represents each and every individual targeted by the vaccination program and provides the only comparable information on key criteria for the targeted and vaccinated individuals. One of the fundamental problems with NIMS is that it contains some people who were 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 referred to as “ghosts” . Because vaccine intake has been so high, even a small number of extra people on the database will increase the number recorded as unvaccinated – this makes the rate of COVID-19 cases seem lower than them in some of the younger unvaccinated groups should be .
- The second major denominator is the Office of National Statistics (ONS), which provides an estimate of the total number of people in each age group mid-year. This is based on the 2011 census and updates the estimates every year using different 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 pose other problems as well. Since the ONS data is not based on a list of unique people, it is not possible to link a COVID-19 case to a person’s vaccination status. This limits any analysis of the recording by a few key criteria. In addition, current estimates seem to count too little in some older age groups. Since COVID-19 rates in the elderly are the ones we need to worry about most, as these age groups are at the highest risk of hospital admissions and death, using the ONS denominator yields some inconsistent age-specific rates for these more severe ones Results.
Neither is perfect, but for estimating the number of cases by vaccination status, we believe that using NIMS to identify the vaccinated and unvaccinated is the best way to provide stable and comparable data, even if we accept that the infection rates are unvaccinated People in younger groups seem lower than the real number. These numbers are useful for planning purposes, such as understanding hospital workloads, but should not be used to assess the effectiveness of the vaccine. Analysis of vaccine efficacy from routine data is only possible by using the variables encoded in NIMS, which are available at an individual level to anyone who presents for a test.
What data should we look at?
Data on COVID-19 hospital admissions and deaths are much less prone to bias because the tests are more complete and it is therefore more valid to compare rates for these serious outcomes. But even so, a properly performed analysis is much more reliable, as explained above.
Our publication of COVID-19 vaccine surveillance data is consistent with all of the other vaccine surveillance data we have published, and this consistency is important in understanding the patterns we see across all of our surveillance data sources. In this way, we have been publishing the data since the beginning of the year, based on other data from vaccine monitoring.
We believe that transparency – coupled with explanation – remains the best way to deal with misinformation. UKHSA is committed to regularly posting our vaccine efficacy data and promptly sharing that evidence with others – this has played a major role in building trust in vaccines in this country and around the world.
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