The study looked at vaccinated and and vaccinated people in Sweden and looked at the event rates up to 9 months.
They calculated vaccine effectiveness at regular intervals until past six months. The authors conclude erroneously that vaccine effectiveness drops to (zero).
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The traditional method of calculating effectiveness is to compare the outcomes in the vaccinated & vaccinated groups and see the percentage difference between the two.
Eg. If 10 events happen in the unvax group and only 1 event occurs in the vax group, effectiveness is 90%.
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However in the real world observational studies, we must remember that unvaccinated group also develops immunity as a result of asymptomatic or symptomatic natural infections.
As a result, the event rate in the unvaccinated population drops.
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The authors of the paper have helpfully provided event rates over each time period, for each sub-group.
I used these event rates to plot a graph which I have linked below.
The graph of the vaccinated group (left, in blue) shows steady effectiveness even after six months.
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However the graph of the unvaccinated group (right, green) is interesting. It shows a relatively high event rate at the onset of the vaccination programme (when natural infections were few).
At about 4 months, we can see the rate drops to equal that of the vaccinated group.
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This decline in event rate is clearly the result of immunity brought about by natural infection.
Unfortunately, when we apply the traditional formula of effectiveness, this gets erroneously interpreted as a “decline in vaccine effectiveness to zero”.
Example 👇
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To explain the fallacy, let me use an example.
Imagine that we are seated in a moving train. As we look to the left, there is another train on the next track, but moving at a slower speed. When we look at that train, we get a sense of our speed. But is that the right method?
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Looking at the train on the parallel track is exactly how vaccine effectiveness is being presently calculated.
Unfortunately this assumes that the other train will continue to move at the same speed throughout the journey.
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What we don’t take into account is that the other train could pick up speed, and this will affect our calculation about our own speed - that is if we continue to use this technique.
This is how vaccine effectiveness is commonly being calculated, including in this paper.
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Now imagine that the next train picks up speed and is moving as fast as ours. As we look to the left, we may think that our train is not moving at all. We may conclude that our train has stopped moving. This is the erroneous conclusion of lack of effectiveness at six months.
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What is the right method then?
What should be done is to look to the right -at stationary objects. If we did that from the beginning, we would know that our train has been moving at a steady speed right from the outset.
We realise there is no decline in our train’s speed.
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The above fallacy is just one of the problems that occur with observational studies. While such studies are important, there are limitations.
Other limitations include variation in behaviour, testing rate, comorbidity and risk tolerance in between groups.
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It is important to look out for any real decline in protection from severe disease & death. We believe this protection is long-term because of memory cells, which continuously improve over time, through affinity maturation, somatic hypermutation and antibody class switch.
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In the real world, natural infection may act as natural boosters of immunity, in both vaccinated & unvaccinated people. Recent data have shown that breakthrough infections induce anamnestic response.
This however does not mean that people should seek out such opportunities.
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Looking at the data presented by the the Swedish paper, it appears that the two populations (vax and unvax) are finally reaching a level ground - at approximately six months - when the event rates (per 100,000 person days) appear to be equalising.
First detailed description of immune response following breakthrough infections. This is a study on a subset of 35 people (infected vs uninfected) from the Provincetown Massachusetts outbreak, US.
At the same time, vaccinated individuals are less likely to be admitted to hospital, or die from COVID-19.
The reported death protection is likely to be an underestimation, because vaccination preferentially occurs among people who have more background illnesses.
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The question is why the rate of infection is higher among vaccinated people.
It is obvious by now that vaccines aren’t very good at stopping the virus from entering the nose or throat, particularly past the initial few weeks of high antibody titres.
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Whether Children should be vaccinated before attending school is a topic where not everyone agrees upon.
In other words this is not a binary topic; which means that a “yes or no” answer is not relevant.
That is why the opinion of doctors who take care of patients matter.
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Experience in my part of India on the ground has overwhelmingly stated the following facts.
1. Regardless of what immunology says, the chance that a child will fall sick from COVID-19 is so rare - it is much rarer than chance of death from many routine things in life.
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When we view the outside world while standing in the ICU, it is easy to be tricked into believing that the whole world is falling severely ill.
It is true that a tiny % of children fall ill, but that % is less than 0.008 (Kerala) and is ~made up of children with comorbidity.
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Which is why if we only look at the severely ill children, we will not be able to see the massive denominator of healthy children who were not affected significantly by the virus.
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Optimal T cell response was detected - that is CD4 Th1 and CD8 with a high degree of polyfunctionality, covering a broad range of spike protein epitopes.
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This increased T cell breadth will help fight variants. In other words, a few viral mutations here or there will not make a difference to these T cells.
This means the virus will continue to be hunted down even if it modified its appearance to gain entry into the body.
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