This seems like one of the hardest things to measure: how many people actually have coronavirus, given your estimate? It's wildly dependent upon testing strategy and delays in the system.
We use the SIR model, a standard epidemiological model, to estimate the disease dynamics.
Compartmental models in epidemiology
The specific flavour we use is the Kermack-McKendrick model:
The crucial factor governing disease spread is R0 (the basic reproduction rate), which is the average number of people somebody with the disease infects. This is a function of the number of susceptible people, the infection rate β and the recovery rate γ.
You can decompose this into how many people an infected person contacts a day, and the transmission probability from a given contact:
β = Probability of transmission x Number of contacts
We allow you to control Number of Contacts per day in the webapp. We have estimated Probability of Transmission from the following numbers:
We can then formulate R0 as:
R0 = Probability of transmission x Number of Contacts per day x Number of infectious days
Subbing in our numbers:
**2.5 = Probability of Transmission x 14 x 10**
we solve for Probability of transmission, which comes out as ~0.018, or 1.8%.