Escape velocity

There is currently lot of debate on how and when we lift restrictions, and the risks of this. There are several unknowns that may affect the outcome. I have extended the model in a couple of simple ways, firstly by including a vaccination effect which both immunises people, and substantially reduces the fatality rate of…

So near and yet not quite…

There’s been quite an amazing turnaround since my last blog post. At the time I wrote that, the Govt was insisting that schools would open as planned (indeed they did open the very next day), and that another lockdown was unthinkable. So my grim simulations were performed on that basis. Of course, the next evening,…

Not even half-way there

Lots of talk from politicians and others that, while not exactly triumphalist, is certainly very positive and enthusiastic about the prospect of vaccinating ourselves out of trouble. Here’s one of the earliest “light at the end of the tunnel” articles for example. And with the new Oxford/AZ vaccine there is renewed excitement. Sorry to pour…

Science breakthrough of the year (runner-up)

Being only a small and insignificant organisation, we would like to take this rare opportunity to blow our own trumpets. Blue Skies Research contributed to one of the runners-up in Science Magazine’s “Breakthrough of the year” review! Specifically, the estimation of climate sensitivity that I previously blogged about here. Obviously, were it not for the…

Modelling the ONS COVID data part 2

Continuing from previously…I have done some upgrades to the method and now have some results that I think are quite acceptable. Most importantly, after thinking about (and getting half-way to implementing) appropriate covariance matrices for the overlapping fortnightly observational summaries, I decided that the most sensible thing to do was just to use a single…

Modelling the ONS COVID data

I’ve grumbled for a while about the ONS analyses of their infection survey pilot (pilot? isn’t it a full-blown survey yet?) without doing anything about it. The purpose of this blog is to outline the issue, get me started on fixing it (or at least presenting my own approach to an analysis) and commit me…

Back to the future

Way back in the mists of time (ie, 2006), jules and I saw what was going on with people estimating climate sensitivity, and in particular how this literature was interpreted by the authors of the IPCC AR4. And we didn’t like it. We thought that any reasonable synthesis should consider the multiple lines of evidence…

Like a phoenix redux

Even odder than finding that our old EnKF approach for parameter estimation was particularly well suited to the epidemiological problem, was finding that someone else had independently invented the same approach more recently…and had started using it for COVID-19 too! In particular, this blogpost and the related paper, leads me to this 2013 paper wherein…

Like a phoenix…

So, the fortnightly chunks in the last post were doing ok, but it’s still a bit clunky. I quickly found that the MCMC method I was using couldn’t really cope with shorter intervals (meaning more R values to estimate). So, after a bit of humming and hawing, I dusted off the iterative Ensemble Kalman Filter…

More COVID-19 parameter estimation

The 2 and now 3-segment piecewise constant approach seems to have worked fairly well but is a bit limited. I’m not really convinced that keeping R fixed for such long period and then allowing a sudden jump is really entirely justifiable, especially now we are talking about a more subtle and piecemeal relaxing of controls.…