A month or two ago I started modelling the reproduction number of COVID-19 using the R0 package. I then used this model to create a Shiny app to break down the data by country. Can we use this information to predict the peak in the UK? For a full detailed explanation see the original article here. But the gist of the process is: model the UK case data using the R0 package fit a linear model to the tail use the model the estimate when the effective reproduction number reaches 1 Here is the current case data as of the 9th of April:

Note this is adapted from an original article that goes into much greater detail. Please check it for the nitty-gritty R code in full. Using Simmer it’s possible to model the performance of a real-world software platform. Simmer is a process-oriented and trajectory-based Discrete-Event Simulation (DES) package for R It allows us to model a process as a “trajectory” an item takes through various stages or “resources” in Simmer parlance.

I have been attempting to understand the nature of the “reproduction number” in epidemiology and to this end I’ve enlisted the help of the R0 package for R. For a good overview of what the reproduction number is and why it is so important please check out this article. This package allows you to estimate R0 given a time series of case counts. I have used the data from the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository in order to perform these calculations.