Coronavirus modelling work reported by the BBC

This article by the BBC’s Rachel Schraer explores the modelling for the progression of the Coronavirus Covid-19. In the article we see some graphs showing epidemic growth rates, and in particular this one showing infection rate dependency on how many one individual infects in a given period. https://www.bbc.co.uk/news/health-52056111 This chart led me to look intoContinue reading “Coronavirus modelling work reported by the BBC”

Coronavirus – possible trajectories

I guess the UK line in the Johns Hopkins chart, reported earlier, might well flatten at some point soon, as some other countries’ lines have. But if we continue at 3 days for doubling of cases, according to my spreadsheet experiment, we will see over 1m cases after 40 days. See:https://docs.google.com/spreadsheets/d/1kE_pNRlVaFBeY5DxknPgeK5wmXNeBuyslizpvJmoQDY/edit?usp=sharingand the example outputs attachedContinue reading “Coronavirus – possible trajectories”

Coronavirus – forecasting numbers

A few people might have seen the Johns Hopkins University Medical School chart on Covid-19 infection rates in different countries. They have produced many different outputs, some of them interactive world incidence models – see https://coronavirus.jhu.edu/map.html. This particular chart usefully compares some various national growth rates with straight lines representing different periods over which theContinue reading “Coronavirus – forecasting numbers”

Coronavirus modelling – GLEAMviz15

Here’s the kind of stuff that the Covid-19 modellers will be doing. https://www.nature.com/articles/srep46076.pdf I have downloaded GleamViz, http://www.gleamviz.org/simulator/client/, and it is quite complicated to set up (I used to have a little Windows app called Wildfire that just needed a few numbers to get a pictorial progression of life/recovery/death from the disease, depending on infectivity,Continue reading “Coronavirus modelling – GLEAMviz15”