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 […]
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
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
Over the last few months, we have been using advanced data intelligence to improve the sourcing, timeliness and validation of Covid-19 statistics. We then use our emergent and adaptive platform to provide high quality predictive modelling of its likely progress. Human nature being what it is, people have become somewhat desensitised to raw numbers and to
Throughout the pandemic, we\’ve watched UK government Covid-19 policy-making as it appears to follow a drunkard’s walk between, on the one hand, an inherent laziness of response and a politically-influenced disinclination to act and, on the other, an attempt to claim some sort of causal relationship with the scientific and real world advice that they\’re
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
In developing our daily-predictive AI for Covid-19 infections , we\’ve come across some, ah, interesting quirks in the official UK data: previously, we\’d been using the government\’s daily download data set for England, hoovering it into udu and thence driving the internal and R-based analytic and learning models. We\’ve done the same for Scotland, Wales
Two Worlds is one of the successful applicants to a £40M fund created to support “Business-led innovation in response to global disruption”, a competition that attracted 8,600 applicants. Working with a team including epidemiologists, mathematical modelling specialists and the Department of Computer Science at Imperial College, Two Worlds is using udu’s intelligent analytic software to
