Adam Kucharski Profile picture
Mathematician/epidemiologist at @LSHTM. @WellcomeTrust fellow and @TEDFellow. Author of The Rules of Contagion. Views own.
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29 Jul
If - and it’s still a big if - exposure notifications from the NHS covid app/T&T were a major factor in driving the recent UK case decline, it’s worth considering what might happen next... 1/
It’s plausible that a rapidly growing epidemic + rapid testing availability + exposure notifications (both formal via T&T/app and informal among friends) has led to large numbers of people who would have been involved in transmission instead quarantining. 2/
If exposure risk is concentrated in time (e.g. because of Euro matches), quarantine timing would also have been concentrated in the period immediately after. Which means we can make a testable hypothesis about what might happen next… 3/
Read 7 tweets
15 Jul
Still see 70% quoted as level of vaccination required for 'herd immunity'. Important to note it's now likely to be much higher. The standard (albeit rough) calculation for herd immunity threshold is (1/E) x (1-1/R) where E is vaccine effectiveness in reducing transmission... 1/
In scenario where R is 6 (plausible for Delta in susceptible populations without any restrictions), and vaccination reduces infection/infectiousness such that onwards transmission reduced by 85%, above calc suggests would need to vaccinate (1-1/6)/0.85 = 98% of population. 2/
If transmission reduction is less than this (which is likely the case for some vaccines against Delta), or R higher, then herd immunity wouldn't be achievable through current vaccines alone. This leads to three possibilities... 3/
Read 6 tweets
12 Jul
One argument put forward for July 19th UK reopening is to bring infections forward to reduce winter wave. To be honest, I’ve always found idea that we could tailor a pandemic to get 'better' sized future waves a bit absurd - whether in spring 2020 or now. A few thoughts... 1/
For me, main issue now is medium term disruption vs medium term epidemic size. Many people now seem OK with R>1 in countries with relatively high vaccination % (at least implicitly, given they aren’t advocating for the strong measures required to guarantee R<1). 2/
Given R>1, much of Europe faces large epidemics likely to end with accumulation of immunity in next few months - much of it from infections. Reopening would accelerate this, but won't be difference between epidemic & no epidemic (unlike, say, reintroducing measures to get R<1) 3/
Read 10 tweets
11 Jul
In discussions of Delta in UK & much of Europe, it's worth remembering that to avoid a large number of future COVID-19 cases at this point, countries would need to dramatically curtail social mixing - otherwise they've still got a rising epidemic, just with a flatter peak. 1/
Look at recent action in Singapore, for example, which has now fully vaccinated 40% of population. Article from May: straitstimes.com/singapore/heal… and last week: straitstimes.com/singapore/heal… 2/
Big difference with UK, of course, is case numbers. Given current case level in UK, if test & trace was suddenly omniscient with full adherence, millions of people would now be in quarantine. In terms of disruptions, it would be somewhat equivalent to a snap ban on gatherings. 3/
Read 6 tweets
4 Jul
I've always found it very unhelpful that 'self-isolation' is used to refer to both isolation and quarantine, but the distinction is now becoming increasingly important... 1/
To recap, isolation is for people who are confirmed to be infected; quarantine is for people who currently seem healthy but may be infected. A stay-at-home order is basically a large, untargeted quarantine (some countries even call it 'community quarantine'). 2/
As vaccines reduce infections/transmission, countries are re-evaluating approaches to disruptive quarantine, whether for travellers or contacts of cases (e.g. in US: cdc.gov/coronavirus/20…). However, we need to be careful about jumbling isolation and quarantine together... 3/
Read 5 tweets
2 Jul
Schools, workplaces, pings from COVID app… Having high UK case numbers over summer will have huge implications for quarantine burden. A few thoughts… 1/ bbc.co.uk/news/business-…
Because vaccines reduce onwards transmission, contacts are becoming less risky on average - which means that for a given value of R, each case will typically have far more contacts than they would have had last year. 2/
Under pre-pandemic contact patterns, a typical case will have 25+ contacts while infectious (thelancet.com/journals/lanin…). That’s a lot of people who could potentially be quarantined per case. 3/
Read 4 tweets
18 Jun
Any discussion of daily testing vs quarantine for contacts of cases in schools needs to address the key epidemiological question: if a child in a school tests positive, what do you do next? 1/
Encouraging ventilation etc. to reduce transmission risk is important, but you still have to decide what to do about a positive result. Do you quarantine their contacts or not? 2/
If you decide to abandon quarantine because you think ventilation etc. has sufficiently reduced risk, then this still means accepting higher transmission risk than if quarantine had remained in place. 3/
Read 8 tweets
11 Jun
How long could UK cases continue to rise? And how might hospitalisations increase alongside? A thread... 1/
Despite relatively high vaccination rates compared to other countries, cases are growing and in many areas R is now above 1.5. Remember, immunity is already 'priced in' to this number - without vaccination and the social distancing still in place, R would be *much* higher. 2/
If R is 1.5 and contacts/control remain the same, then we'd need remaining part of the population who could potentially spread COVID to shrink by at least 33% before R drops below 1 & epidemic peaks. This would require additional immunity, either from infections or vaccines. 3/
Read 9 tweets
5 Jun
A common Q: “how can COVID hospitalisations in UK still grow if vaccine % high?” Answer: look at the data. Average was ~120 daily COVID admissions over past week. These would have been infected about 2-3 weeks earlier, when case numbers ~2000 per day. This shows two things... 1/
First, there was still a group at risk of hospitalisation a few weeks ago. And second, this risk was large enough to show up as hundred of admissions in recent data, even though cases were at relatively low levels. 2/
So the key question here: if case numbers were to grow X times larger, why wouldn’t hospitalisations also grow X times larger? 3/
Read 4 tweets
25 May
One thing that has hugely shaped countries' response to COVID, and which I don't think gets enough discussion: genuine constraints and perceived constraints. A thread... 1/
Some apparent local constraints have persisted throughout the pandemic. For example if you look globally, there are still notable differences in approaches to surveillance and quarantine... 2/

It's worth reading these papers on the response in Taiwan (jamanetwork.com/journals/jama/…) and Korea (jamanetwork.com/journals/jama/…). Should more countries include these data-intense approaches in future pandemic plans? Or does reluctance to date reflect an immovable constraint? 3/
Read 9 tweets
23 May
Preliminary UK data on vaccine effectiveness against B.1.617.2 (originally detected in India) now available: khub.net/documents/1359…. A few things to note... 1/
First and foremost, it’s another reminder that *second doses matter*. By Aug/Sep, UK will be in much better position against B.1.617.2, but there’s a risk of substantial transmission in meantime as things reopen. 2/

Also remember that when vaccine effectiveness high, small absolute differences can have big effect. E.g. a drop from 95% to 90% would double number at risk (and probably more than double outbreak size given non-linear nature of transmission). 3/
Read 6 tweets
18 May
In real-time, epidemic data streams are patchy, delayed, biased and often contradictory. That's why scientists use terms like 'realistic possibility', 'medium confidence' etc. Uncertainty is inevitable (although will reduce over time) - and yet decisions still need to be made. 1/
B.1.617.2 has been spreading fast in some areas, and people are working hard to disentangle causes & quantify exactly what it means for wider transmission. Control measures are now both going in (e.g. testing, vaccination) & being relaxed, which making analysis even trickier. 2/
For more info, people like @kallmemeg @arambaut @jburnmurdoch @erikmvolz @TWenseleers have been posting some useful summaries recently: 3/
Read 4 tweets
11 May
Have recently been thinking more about the transmissibility of endemic seasonal coronaviruses... antibody positivity increases sharply at a relatively low age, suggesting high transmissibility in susceptibile populations (below from: nature.com/articles/s4146…). 1/
Older groups have built immunity to seasonal CoVs, but above suggests R0 (i.e. R in fully susceptible population) could be quite high for these viruses. Possibly so high that even stringent measures wouldn't be enough to control in susceptible pop? 2/
If so, it would be yet another reminder of the importance of equitable, fast vaccination globally to reduce the future impact of COVID-19. 3/3
Read 4 tweets
5 May
One subtlety of below issue that’s worth highlighting – targeted travel bans (as opposed to near-total border closures) have played out in much the way we’d have expected pre-COVID, delaying rather than stopping local epidemics. A few thoughts… 1/

In December, many countries reactively banned travel from the UK (theguardian.com/uk-news/2020/d…), but this didn’t stop the rise of B.1.1.7 across the continent (nytimes.com/interactive/20…). 2/
As noted by @firefoxx66 at the time, targeted bans can delay introductions, but this will be of limited use if measures aren’t also in place to deal with (undetected) local circulation: 3/
Read 8 tweets
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
26 Apr
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/

Read 4 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