- Stephen Grice

# Help - About the Math

Updated: May 11

SIR (Susceptible-Infected-Recovered) modelling is highly effective at predicting disease spreading through populations including COVID-19.

The simulation tool uses a modified version of the SIR model with parameters developed for New Zealand conditions by Professor Hendy's group at the University of Auckland called __Te Punaha Matatini __[TPM]. For more details on this deterministic model which was last updated on the 30 March 2020, see __here__. The parameters used in the Hendy model are __here__.

TPM has also released a simulator application __here__.

As with any of these models they are only as good as the input parameters. There are several parameters that go into this model, but the most important by far is basic reproduction number, RO.

The value of R0 is a number that is intrinsic to the disease and the population under study. For measles R0 is 12-18, an very high number that represents an extremely infectious disease. The best information available is that the R0 for COVID-19 internationally is about 2.5. In New Zealand it is thought to be a bit higher.

If R0 > 1 for COVID-19 then the numbers disease will exponentially increase over time. If R0 < 1 then the disease will fade away. So the choice of this parameter is critical to modelling and planning for the future.

In the simulation tool, the value of R0 can be obtained by multiplying the beta value by 10.15 (accepting other constants). The simulation tool allows you to choose any input values (initial conditions) and to see the predictions as a function of time.