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Job request: 16702

Organisation:
Bennett Institute
Workspace:
vax-fourth-dose-rd-baseline
ID:
ajhegn2wfny2zurd

This page shows the technical details of what happened when authorised researcher Andrea Schaffer requested one or more actions to be run against real patient data in the 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 marked as 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.

Jobs

  • Action:
    covid_outcomes
    Status:
    Status: Succeeded
    Job identifier:
    4g2lrutb74g65yay

Pipeline

Show project.yaml
######################################

# This script defines the project pipeline - it specifies the execution orders for all the code in this
# repo using a series of actions.

######################################


version: '3.0'

expectations:
  population_size: 100000

actions:

# Generate study population and extract baseline characteristics at Sep 3, 2022
  generate_study_pop_baseline:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition_baseline
      --output-dir=feather 
      --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_baseline.feather
      
# Data cleaning, defining exclusions, saving final study pop
  data_process_baseline:
    run: r:latest analysis/processing/data_process_baseline.R
    needs: [generate_study_pop_baseline]
    outputs:
      highly_sensitive:
        cohort: output/cohort/cohort_*.csv
      moderately_sensitive:
        descriptive: output/descriptive/total_*.csv

 # Extract outcomes pre-campaign (index date = Sep 3)
  outcomes_sep:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition_outcomes_1
      --index-date-range "2022-09-03" 
      --output-dir=feather 
      --output-format=feather
    needs: [data_process_baseline]
    outputs:
      highly_sensitive:
        cohort: output/index/input_*.feather

 # Extract outcomes mid-campaign (index date = Oct 15)
  outcomes_oct:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition_outcomes_1
      --index-date-range "2022-10-15" 
      --output-dir=feather 
      --output-format=feather
    needs: [data_process_baseline]
    outputs:
      highly_sensitive:
        cohort: output/index/input*.feather

 # Extract outcomes during-campaign (index date = Nov 26)
  outcomes_nov:
    run: cohortextractor:latest generate_cohort
      --study-definition study_definition_outcomes_2
      --index-date-range "2022-11-26 to 2023-01-31 by week" 
      --output-dir=feather 
      --output-format=feather
    needs: [data_process_baseline]
    outputs:
      highly_sensitive:
        cohort: output/index/inpu*.feather

# Data cleaning of outcome data
  data_process_outcomes:
    run: r:latest analysis/processing/data_process_outcomes.R
    needs: [outcomes_sep, outcomes_oct, outcomes_nov]
    outputs:
      highly_sensitive:
        outcomes: output/cohort/outcomes*.csv

# Plots of COVID booster uptake by age
  booster_uptake:
   run: r:latest analysis/descriptive/cumulative_vax_byage.R
   needs: [data_process_baseline]
   outputs:
      moderately_sensitive:
        rates_csv: output/cumulative_rates/final_*.csv 
        plot: output/cumulative_rates/plot_*.png

# Outcome plots #
  covid_outcomes:
   run: r:latest analysis/descriptive/plot_outcomes_byage.R
   needs: [data_process_outcomes]
   outputs:
      moderately_sensitive:
        measure_csv: output/covid_outcomes/plot_*.csv
        plot: output/covid_outcomes/plot_*.png

# Discontinuity of demographics
  # demographics:
  #  run: r:latest analysis/descriptive/demographics_byage.R
  #  needs: [generate_study_pop_baseline, data_process_baseline]
  #  outputs:
  #     moderately_sensitive:
  #       measures_csv: output/descriptive/demographics_*.csv


# Flu vaccine uptake #
  # flu_vax:
  #  run: r:latest analysis/descriptive/flu_vax_byage.R
  #  needs: [generate_study_pop]
  #  outputs:
  #     moderately_sensitive:
  #       measure_csv: output/cumulative_rates/flu_*.csv
  #       plot: output/cumulative_rates/plot_flu_vax_byage.png

# ITT analysis #
  # itt_analysis:
  #  run: r:latest analysis/statistical_analysis/itt_analysis.R
  #  needs: [data_process_outcomes]
  #  outputs:
  #     moderately_sensitive:
  #       measure_csv: output/covid_outcomes/outcome_*.csv

# Outcome plots #
  # covid_outcomes:
  #  run: r:latest analysis/descriptive/covid_outcomes_byage.R
  #  needs: [generate_study_pop]
  #  outputs:
  #     moderately_sensitive:
  #       measure_csv: output/covid_outcomes/covid_*.csv
  #       plot: output/covid_outcomes/plot_outcomes_*.png
  




# IV analysis #

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 00:04:20

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job information

Status
Succeeded
Backend
TPP
Requested by
Andrea Schaffer
Branch
Protocol-updates
Force run dependencies
No
Git commit hash
40e5edb
Requested actions
  • covid_outcomes

Code comparison

Compare the code used in this Job Request