This page shows the technical details of what happened when authorised researcher Alex Walker requested one or more actions to be run against real patient data in the Long COVID-19 project, within a secure environment.
By cross-referencing the indicated Requested Actions with the Pipeline section below, you can infer what
security level various outputs were written to. Outputs
highly_sensitive can never be viewed directly by a
researcher; they can only request that code runs against them. Outputs marked as
moderately_sensitive can be
viewed by an approved researcher by logging into a highly secure environment. Only outputs marked as
moderately_sensitive can be requested for release to the public, via a controlled output review service.
Show Hide project.yaml
version: '3.0' expectations: population_size: 2000 actions: generate_cohort: run: cohortextractor:latest generate_cohort --study-definition study_definition_cohort outputs: highly_sensitive: cohort: output/input_cohort.csv count_by_strata: run: python:latest python analysis/all_time_counts.py needs: [generate_cohort] outputs: moderately_sensitive: table: output/counts_table.csv practice_distribution: output/practice_distribution.csv per_week: output/code_use_per_week_long_covid.csv per_week_pvf: output/code_use_per_week_post_viral_fatigue.csv code_table: output/all_long_covid_codes.csv practice_summ: output/practice_summ.txt # # to be run locally generate_report_notebook: run: jupyter:latest jupyter nbconvert /workspace/analysis/long_covid_coding_report.ipynb --execute --to html --output-dir=/workspace/released_outputs --ExecutePreprocessor.timeout=86400 --no-input outputs: moderately_sensitive: notebook: released_outputs/long_covid_coding_report.html
State is inferred from the related Jobs.
Timings set to UTC timezone.
- Runtime: 01:29:50