  Real-time forecasting of disease outbreaks requires standardized outputs
generated in a timely manner. Development of pipelines to automate infectious
disease forecasts can ensure that parameterization and software dependencies
are common to any execution of the forecasting code. Here we present our
implementation of an automated cloud computing pipeline to forecast infectious
disease outcomes, with examples of usage to forecast COVID-19 and influenza
targets. We also offer our perspective on the limits of automation and
importance of human-in-the-loop automated infectious disease forecasting.
