A reminder that to estimate COVID vaccine effectiveness, we need to compare risk in unvaccinated and vaccinated groups in same population. Here are a couple of common mistakes to watch out for... 1/
You can't get an estimate of effectiveness by simply comparing how many people have been vaccinated and how many cases/hospitalisations there have been in this group (because, of course, if there's no local COVID transmission, you'd always estimate a 100% effective vaccine). 2/
Nor can you just look at what proportion of cases have been vaccinated, because effectiveness will also depend on what proportion of the population have been vaccinated. 3/

Some examples of estimation of vaccine effectiveness in the UK context: medrxiv.org/content/10.110… & assets.publishing.service.gov.uk/government/upl… 4/4

• • •

Missing some Tweet in this thread? You can try to force a refresh

Keep Current with Adam Kucharski

Adam Kucharski Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!


Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @AdamJKucharski

28 Apr
How long does immunity to SARS-CoV-2 last (and how long might it last in future)? A few thoughts... 1/
We now have data from several cohort studies showing responses can last over a period of several months at least. E.g. "Based on data currently available, a rapid decline of SARS-CoV-2 IgG seropositivity or neutralising capacity has not been seen." thelancet.com/journals/lanin… 2/
And "immune memory in three immunological compartments remained measurable in greater than 90% of subjects for more than 5 months after infection" science.sciencemag.org/content/371/65… 3/
Read 8 tweets
20 Apr
There’s still uncertainty about how much protection various COVID vaccines give against certain variants of concern (e.g. B.1.351 identified in SA & P.1 in Brazil). So where will new real-life evidence on vaccine effectiveness against variants come from? A few thoughts...1/
First we need to be clear what type of protection we're talking about (see below: ) – protection against infectiousness will shape transmission dynamics, whereas protection against severe disease will influence outcomes like hospitalisations and deaths. 2/
Much of the evidence to date about different forms of protection against variants has come either from lab studies of immune responses or secondary data from vaccine trials. Both are useful, but also have some limitations... 3/
Read 14 tweets
14 Apr
If populations are highly vaccinated, we'd expect a higher proportion of future cases to have been previously vaccinated (because by definition, there aren't as many non-vaccinated people around to be infected). But what sort of numbers should we expect? A short thread... 1/
In above question, there are a lot of things happening conditional on other things happening (e.g. probability cases have been vaccinated), which means we can use Bayes rule (en.wikipedia.org/wiki/Bayes%27_…) to work out the proportion of cases that we'd expect to have been vaccinated. 2/
If we want to know the probability of event A given event B, or P(A|B) for short, we can calculate this as

P(A|B) = P(B|A) P(A)/ P(B)

There are a couple more mathsy tweets coming up, so hold on as then we'll get back to the real-life implications. 3/
Read 9 tweets
6 Apr
The debate around tracking infection/vaccine status for events is reminiscent of last year’s debate around privacy & contact tracing apps. Ultimately, the better countries' ability to track where infection is/isn’t, the lower their COVID risk will be. 1/
If people don’t want to collect/use data in this way, they need to accept the trade off will be a higher COVID risk in the community (or more disruptive measures to prevent that risk). 2/
Many countries have implicitly chosen to introduce stay-at-home orders or live with higher numbers of cases rather than use detailed surveillance (e.g. to identify infections linked to superspreading events or enforce quarantine). 3/
Read 4 tweets
24 Mar
This is an interesting perspective on Taiwan (& glad it mentions data/privacy), although I'd like to see more references to what local officials were actually saying about approach in real-time, rather than what UK-based researchers later say it was: theguardian.com/world/2021/mar… 1/
E.g. from April 2020: "Covid-19 is becoming flu-like. It means that since it is highly contagious with many mild or asymptomatic cases, and can be transmitted through droplets and contaminated areas, we won’t get rid of this virus totally." telegraph.co.uk/global-health/… 2/
Taiwan has implemented several innovative, effective measures against COVID-19, but it will harm our ability to plan for the next pandemic if we don't look fully at how countries were interpreting - and acting on - available evidence in real-time. 3/
Read 4 tweets
16 Mar
Is “we couldn’t have predicted the emergence of B117” a scientifically accurate statement? 1/
I’d argue it depends whether statement is interpreted in general or specific terms. “We couldn’t have predicted the possibility of a phenotypically distinct SARS-CoV-2 variant” is clearly inaccurate (given some adapation would have been involved in its original emergence)... 2/
...but “we couldn’t have predicted a variant emerging when it did in autumn 2020 with B117’s specific characteristics” is entirely reasonable (especially as our knowledge of its characteristics is still developing). 3/
Read 4 tweets

Did Thread Reader help you today?

Support us! We are indie developers!

This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!