Tag Archives: pandemic

Portrait of a Pandemic Out of Control

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.

Which is the point: this is a dynamic system with both momentum from existing infections and where rising (or falling) infection rates cause case rate to accelerate or decelerate. So we brushed up on our Newtonian physics and used his first and second Laws of Motion to calculate the momentum and its force – the acceleration or deceleration of the pandemic – at any time.

So the graph below shows the energy (blue) and acceleration (pink) of the pandemic across the UK from 1st April 2020. The equivalent maps show that, while the pandemic is decelerating in the South-East (and accelerating slightly in the NW and Scotland), the level of energy in the SE is still huge (and effectively off the scale relative to the first wave in March-May, showing that it would take very little for the pandemic to start to turn up again)

Kinetics and force of the Covid-19 pandemic in the UK, from 2020-04-01 to 2021-01-08
Momentum of the Covid-19 pandemic in the UK as of 2021-01-09
Force (acceleration/deceleration) of the Covid-19 pandemic across the UK, as of 2021-01-09

When we started experimenting with this approach, we expected something. We didn’t quite expect such a dramatic visualisation, especially one that subjectively feels to have a strong correlation with real world impact, hopefully bringing that home for non-experts, and at a visceral level.  Remember here that the UK currently has about the world’s highest case rate – well ahead per capita of the USA.

We’ve been over our methodology and believe that we’re calculating both reasonably and accurately.

Time for a different approach?

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?