The UK government has just announced that it isn’t going to make a decision on further relaxing Covid-19 restrictions for another two weeks, just as many people were, quite reasonably hoping that the fat lady was, if not in full song, at least warming up for her aria.
Flippancy aside, let’s be clear: delaying a decision like that is utter nonsense, at multiple levels: whether it’s driven by the use of lagging data, the continuing failure to adopt and use effective forecasting (ours or anyone else's), the pursuit of political dogma, or any combination of these, they're once again delaying decision making until it's too late.
Worse, they seem to be relying on the success of the vaccination program to try to pull a largely fictional rabbit out of their hat - the hat that comes with a large label saying, "Wishful Thinking". But now for the data and analysis…Continue reading Waiting for the Fat Lady→
The UK government stated yesterday (13 May) that rising case numbers in the Bolton area were a cause for concern, and that very many of these cases were of the so-called ‘Indian’ variant (B.1.617.2 being the designated variant of concern, with B.1.617.1 and B.1.617.3 under investigation). Here, raw data for case numbers has been available for weeks, with organisations such as the Sanger Institute also providing a very informative breakdown by sequenced variants.
Our analytics platform had identified Bolton and other areas as potential concerns more than two weeks ago and had flagged a correlation between these hot spots and the ethnic balance of the local population, such that, even in the absence of cross-border travel data, of the emerging variants or the situation in India, we were able to provide early warning of emerging problems.
Which very much begs the question as to why the UK government only raised this yesterday, and why travel restrictions from India were only imposed long after the pandemic reached critical mass there.Continue reading Early Warning Onwards→
A remaining big unknown in the pandemic is not whether vaccines reduce serious symptoms, hospital admissions and deaths – they do – but whether and to what degree vaccines reduce the ability of those vaccinated to infect others, whilst not being symptomatic themselves. As we've noted before, initial data on post-vaccination infectivity was somewhat contradictory, so we don't yet build the impact of vaccination on infectivity into our forecasting.
SAGE announced today that England's R number has risen across to between 0.8 and 1. They update their pronouncements once a week, based on their modelling from data that's even further behind.
We take a different approach: we use emergent and inferential analysis to generate R number calculations and 28-day forecasts, on a daily basis, for every local authority in the UK.
We can say that England, as of today, is at an R number of around 0.92, up from a low of 0.80 on 19 April. Our forecasting suggests that it's going to go over 1.0 from tomorrow, reaching roughly 1.3 by the end of the month, with England leading the way, followed by Wales and Northern Ireland, with Scotland doing rather better, for the moment at least.
The time to relax lockdown is once you have a combination of low case numbers (check), an R (infectivity) number that’s well below 1 and trending downwards, and have effectively stamped on any potential hot spots around the country, to the point where the increased travel between areas that we're already seeing doesn't risk a spread from those hot spot areas acting as reservoirs of reinfection.
There’s been a lot of covoptimism this past week, from assorted government spokesfolks, including from people who do know what they’re talking about – a prime example being Prof. Neil Ferguson of Imperial. The theme here is that cases, case rates and the R number have been falling strongly and appear to be continuing to do so.
That’s true, to a point. But our modelling suggests that the immediate future is less rosy.
It's not about the data – we use the same published sources as the government, albeit that they've got access to more sources than we do – it's more about what you do with it.
Another Friday update: we’re well into our private Beta of our predictive analytics and what-if? modelling system for Covid-19 analytics.
So what is it telling us today?
As of 3rd February our projections are (within their confidence limits, which of course become broader the further out we look, even if the central projection is tracking the reality curve well), that the R number bottoms out about now for the UK as a whole, with case numbers continuing to fall until around the 9th, by which time R number is back to .92 and, by the 13th, it's more likely to be above 1 again, mostly driven by the SE (Essex particularly) and Merseyside (see header picture).
On Friday 29th January, the Scottish Government announced that Na h-Eileanan Siar (the Western Isles) is being put into Level 4 lockdown, following a surge of new cases.
On the basis of the data available to us and our modelling approach, we're not convinced about this decision: it appears to have be made on the basis of out-of-date analysis in an area which turned the corner on this outbreak some time ago.
Our emergent analytics, which generate fresh outlooks every day, suggest that the peak of the outbreak here was passed on 19th January and that it has declined, on multiple metrics, since then.
We’ve been thinking for some time about how best to present the dynamic of the pandemic in a way that actually shows what's happening – the R number doesn't give any idea of magnitude and is - in our opinion – best kept behind the scenes as a contributor to analytic models, raw or compensated case numbers are just that – daily records – shocking enough in themselves but they still don't show the energy in the thing. Continue reading Kinetics of a Pandemic→
We – as a society – had the opportunity to prevent SARS-CoV-2 becoming endemic. We largely wasted it, initially by not locking down early enough or for long enough to remove it from the population. Nor did we use the lockdown period to set up effective data collection, testing, tracking and analytic tools to enable rapid and fine-grained response to predicted changes in incidence (it's a truism that, by the time you're working with actual data, you're already behind in your response).
Public policy decisions are therefore based on incomplete and lagging data, partial models and on individual and committee opinion (however well qualified the participants) rather than being informed by data-driven modelling of potential outcomes. We are also behaving as though we're dealing with a static target rather than a continuously evolving situation, one where an unintended consequence of partial and incomplete restrictions is that it effectively selects for different strains of the virus, as it evolves to cope with changes in population behaviour. This virus, like any other, has been mutating since before it collided head-on with our species, and it continues to evolve as it seeks selective advantage in exploiting its human host population, at any given time. Continue reading Time for a different approach?→
Two Worlds is an AI research consultancy and incubator, specialising in complex, adaptive systems. We create strategies, technologies and services that encompass advanced data discovery and fusion AI/Machine Learning, IoT networks, augmented and mixed reality systems.