dansk-register

A platform for epidemiological studies on the Danish national registers, and the study pipelines built on it.

The package contains no data. It is the code that reads a register delivery inside a secure research environment, builds cohorts and outcomes from it, and estimates and reports the results.

What is in it

The dependency direction is one way and enforced by a test: the platform never imports a study, and studies never import each other. Code that turns out to be general is lifted into dansk_register rather than shared sideways.

Install

pip install dansk-register
pip install "dansk-register[figures]"   # adds matplotlib for figure rendering

The figures extra is optional on purpose. The estimators are written in polars and validated against R, so the pipeline itself carries no numeric stack; matplotlib brings numpy and is needed only to draw. Without it every result is still produced and the figure stage records that it could not render.

Commands

edu-labour --list-profiles                          # what each profile runs
edu-labour-preflight --raw-root PATH                # what a delivery contains
edu-labour --output-dir RUN --profile production \
    --raw-root PATH --allow-expensive-stages --resume
edu-labour-figures --bundle RUN/outputs/export --out figures

societal-costs --output-dir RUN --profile production

Add --dry-run to any edu-labour invocation to resolve the plan and settings without touching data.

Design notes

Stages talk through files. Every stage writes named artifacts into a run directory and reads its inputs from there, so any stage can be re-run alone against a previous run's outputs, and --resume can skip what is already done.

Estimators are written against polars. Aalen-Johansen, Fine-Gray, Cox and the multi-state occupancy are implemented directly rather than taken from a modelling library, and each is validated against reference values from R with those values checked into the tests. That keeps the numbers checkable line by line and avoids a dependency that may not install in an offline environment.

Disclosure control is part of the pipeline. Results leave the secure environment as a bundle of CSV tables with small cells suppressed and the estimates resting on them blanked. Figures are rendered from that bundle rather than from the raw artifacts, so a figure cannot show what the table beside it was not cleared to show.

Status

Research code, developed alongside the studies it implements. The public API is not stable.

Licence

MIT. See LICENSE.