Visualisation based on Hadean's macro-scale simulation of COVID-19, which models the spread of the disease between individuals. It looks at the changing number of infected indivuduals throughout a pandemic and how different policies can be used to lower the number of infections.
The R value can be used to predict how rapidly infectious diseases will spread through a population. There are two components to the R value, Rt and R0. R0 is the base repoductive rate, it measures a disease's potential to spread, if it is above one then the number of cases will grow exponentially, if it is below one the number of cases will diminish so the disease will no longer be prevalent in a population. Estimates of the R0 value of COVID-19 have placed it between 2 and 3.
Rt measures a disease's ability to spread, it looks at how measures put in place to prevent the disease's spread actually work. Rt is made up of four parameters, susceptibility, transmission probability, number of contacts per day and duration of infection. By reducing these numbers, such as going into lockdown to lower number of contacts per day or wearing masks to lower transmission rate, the Rt value can be lowered. The aim is to lower Rt below one as then the disease will eventually dissipate from a population.
Using the visualisation we can easily see how the parameters can not only affect the Rt value, but also when they will affect the peak of the disease, which can help monitor healthcare systems and how they will affect the fatality rate.