Live coding, Emacs, and ghci
Feb 19, 2018
This semester I'm co-lecturing Declarative Programming (COMP90048). The topics I'll be covering include monads, laziness, performance, and type system expressiveness, with Haskell as our language of choice. This will be the first time that I'll try live coding in front of students, because I've previously lectured non-programming subjects such as multi-variable calculus and infectious disease modelling.
Infectious disease forecasting has been a very active research area in the
past few years, and these methods have the potential to provide valuable
decision-support capabilities for public health staff.
There are many challenges that must be surmounted before this can be realised,
and one major gap in the literature is operational research in pilot,
We report on exactly this kind of study in our most recent forecasting paper,
“Epidemic forecasts as a tool for public health: interpretation and
(re)calibration”, which has just
been made available online and will appear in an upcoming issue of the
Australian and New Zealand Journal of Public Health.
In thinking about the strengths and limitations of different surveillance
systems — from the perspective of infectious disease forecasting in my case,
but the point applies more generally — it becomes clear that there is
no silver bullet.
No one surveillance system will tell us everything we need to know in order to
understand the current impact of a disease on a population, or to predict the
future impact of a disease.
The surveillance pyramid
model illustrates this in a very nice and clear manner: