This repository explores absolute risks of various COVID-19 outcomes (mortality, hospitalisation) using the OpenSAFELY data. A key part of this explores risks of COVID-19 mortality and hospitalisation among people with learning disability.
This is the code and configuration for our paper, details of which will be available here.
- Raw model outputs, including charts, crosstabs, etc, are in
released_outputs/ - If you are interested in how we defined our variables, take a look at the study definition; this is written in
python, but non-programmers should be able to understand what is going on there - If you are interested in how we defined our code lists, look in the codelists folder.
- Developers and epidemiologists interested in the framework should review the OpenSAFELY documentation
The OpenSAFELY framework is a secure analytics platform for electronic health records research in the NHS.
Instead of requesting access for slices of patient data and transporting them elsewhere for analysis, the framework supports developing analytics against dummy data, and then running against the real data within the same infrastructure that the data is stored. Read more at OpenSAFELY.org.