Skip to content

Probabilistic ensemble forecasting of Australian COVID-19 cases

Notifications You must be signed in to change notification settings

robjhyndman/covidtalk

Repository files navigation

Probabilistic ensemble forecasting of Australian COVID-19 cases

Talk for the International Symposium on Forecasting, 29 June 2021 and the Australian and New Zealand Statistics Conference, 8 July 2021.

In March 2020, I joined a team responsible for providing probabilistic forecasts of COVID-19 cases to all Australian state & territory Chief Health Officers. We use case-level data of all Australian positive COVID cases, along with nationwide surveys and mobility data from Google, Facebook and Apple. Three separate models have been built: (1) a stochastic susceptible-exposed-infectious-recovered (SEEIIR) compartmental model; (2) a stochastic epidemic model; and (3) a global autoregressive model based on public case data from 31 countries. These are then combined into a mixture ensemble to generate probabilistic forecasts of daily cases which are provided to the Australian governments each week. I will discuss the ensemble forecasting aspects of this work and how we evaluate the results.

About

Probabilistic ensemble forecasting of Australian COVID-19 cases

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published