Stan is a probabilistic programming language widely used for Bayesian modelling and inference. While Stan excels at expressing complex statistical models, reading and understanding Stan code involves becoming familiar with the specific way models are written down, creating a barrier to using and contributing to models written in Stan.

Our team’s work relies a lot on GitHub Actions. Besides the usual workflows to check our code for errors after each push ¹ , we also have many workflows set up to run on a schedule.

31 March, in just under a weeks time, will mark the last day we are producing global national and subnational Rt estimates and nowcasts at https://epiforecasts.io/covid/posts/global/ - more than 2 years after we published the first set of estimates. This is a good opportunity to reflect on what we have learned from this, what went well and what went wrong, and what we would aim to do better next time.

On 10th November, 2017, a suspected case of diphtheria was reported at a Médecins Sans Frontières (MSF) clinic in Cox’s Bazar district, Bangladesh (Finger et al. 2019). A bacterial infection, diphtheria was a major cause of childhood illness and death in the early 20th Century, before a vaccine was developed in the 1920s, then included in the WHO’s Expanded Programme on Immunization in the 1970s.