Job request: 23803
- Organisation:
- The London School of Hygiene & Tropical Medicine
- Workspace:
- covid_collateral_hf_update
- ID:
- t3crsscsmpnkpqnx
This page shows the technical details of what happened when the authorised researcher Emily Herrett requested one or more actions to be run against real patient data in the project, within a secure environment.
By cross-referencing the list of jobs with the
pipeline section below, you can infer what
security level
various outputs were written to. Researchers can never directly
view outputs marked as
highly_sensitive
;
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
-
- Job identifier:
-
ayawp4m74gnpstrv
Pipeline
Show project.yaml
version: '3.0'
# Ignore this`expectation` block. It is required but not used, and will be removed in future versions.
expectations:
population_size: 10000
actions:
generate_dataset_prepandemic:
run: ehrql:v1 generate-dataset analysis/dataset_definition_prepandemic.py --output output/dataset_prepandemic.csv
outputs:
highly_sensitive:
dataset: output/dataset_prepandemic.csv
generate_dataset_pandemic:
run: ehrql:v1 generate-dataset analysis/dataset_definition_pandemic.py --output output/dataset_pandemic.csv
outputs:
highly_sensitive:
dataset: output/dataset_pandemic.csv
generate_dataset_postpandemic:
run: ehrql:v1 generate-dataset analysis/dataset_definition_postpandemic.py --output output/dataset_postpandemic.csv
outputs:
highly_sensitive:
dataset: output/dataset_postpandemic.csv
generate_dataset_escalation:
run: ehrql:v1 generate-dataset analysis/dataset_definition_drug_escalation.py --output output/dataset_drug_escalation.csv
outputs:
highly_sensitive:
dataset: output/dataset_drug_escalation.csv
# Generate datasets for analysis 001
generate_analysis_datasets:
run: stata-mp:latest analysis/001_cr_define_covariates_cohorts.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_dataset_escalation]
outputs:
highly_sensitive:
log1: logs/001_cr_define_covariates_cohorts.log
data1: output/prepandemic.dta
data2: output/pandemic.dta
data3: output/postpandemic.dta
data4: output/drug_escalation.dta
# Drug prevalence dataset: 102
generate_drugprevalence:
run: stata-mp:latest analysis/102_cr_drug_prevalence_or.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/102_cr_drug_prevalence_or.log
data1: output/tabfig/prevalences_summary_prepandemic_redacted_rounded_or.csv
data2: output/tabfig/prevalences_summary_pandemic_redacted_rounded_or.csv
data3: output/tabfig/prevalences_summary_postpandemic_redacted_rounded_or.csv
# Drug prevalence dataset: 102A
generate_drugprevalence_coms:
run: stata-mp:latest analysis/102_A_cr_drug_prevalence_contraind_combinations.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/102_A_cr_drug_prevalence_combinations.log
data1: output/tabfig/combinations*.csv
data2: output/tabfig/pillars*.csv
# Drug prevalence dataset: 102B
generate_drugprevalence_duration:
run: stata-mp:latest analysis/102_B_cr_drug_prevalence_duration.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/102_cr_drug_prevalence_duration.log
data1: output/tabfig/prevalences_summary_prepandemic_redacted_rounded_duration.csv
data2: output/tabfig/prevalences_summary_pandemic_redacted_rounded_duration.csv
data3: output/tabfig/prevalences_summary_postpandemic_redacted_rounded_duration.csv
# Cohort rates: 103
generate_rates:
run: stata-mp:latest analysis/103_cr_cohort_rates_repeated.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/103_cohort_rates_repeated.log
data1: output/tabfig/rates_repeated_prepandemic_redacted_rounded.csv
#data2: output/tabfig/rates_repeated_pandemic_redacted_rounded.csv
#data3: output/tabfig/rates_repeated_postpandemic_redacted_rounded.csv
# Cohort rates in diabetes: 103A
generate_rates_A:
run: stata-mp:latest analysis/103_A_cr_cohort_rates_repeated_diabetes.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/103_A_cohort_rates_repeated_diabetes.log
data1: output/tabfig/rates_repeated_pandemic_redacted_rounded_diabetes.csv
data2: output/tabfig/rates_repeated_prepandemic_redacted_rounded_diabetes.csv
data3: output/tabfig/rates_repeated_postpandemic_redacted_rounded_diabetes.csv
# Cohort rates in those without diabetes: 103B
generate_rates_B:
run: stata-mp:latest analysis/103_B_cr_cohort_rates_repeated_nodiabetes.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/103_B_cohort_rates_repeated_nodiabetes.log
data1: output/tabfig/rates_repeated_pandemic_redacted_rounded_nodiabetes.csv
data2: output/tabfig/rates_repeated_prepandemic_redacted_rounded_nodiabetes.csv
data3: output/tabfig/rates_repeated_postpandemic_redacted_rounded_nodiabetes.csv
# Cohort rates in each overall cohort: 103C
generate_rates_C:
run: stata-mp:latest analysis/103_C_cr_cohort_rates_repeated_stratified.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/103_C_cohort_rates_repeated_stratified.log
data1: output/tabfig/rates_repeated_pandemic_redacted_rounded_stratified.csv
data2: output/tabfig/rates_repeated_prepandemic_redacted_rounded_stratified.csv
data3: output/tabfig/rates_repeated_postpandemic_redacted_rounded_stratified.csv
# Generate table 1 :104
generate_table1:
run: stata-mp:latest analysis/104_cr_table1.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/104_cr_table1.log
data1: output/tabfig/table1_prepandemic_redacted_rounded.csv
data2: output/tabfig/table1_pandemic_redacted_rounded.csv
data3: output/tabfig/table1_postpandemic_redacted_rounded.csv
# Generate table 1 :104B
generate_table1_escalation:
run: stata-mp:latest analysis/104_B_cr_table1_escalation.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/104_B_cr_table1_escalation.log
data1: output/tabfig/table1_drug_escalation_redacted_rounded.csv
# Drug graphs: 105
generate_druggraphs:
run: stata-mp:latest analysis/105_cr_drug_prevalence_graphs.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets, generate_drugprevalence]
outputs:
highly_sensitive:
log1: logs/105_cr_graphs.log
moderately_sensitive:
Figures1: output/tabfig/*_prevalences_by_drug_*.svg
Figures2: output/tabfig/prevalences_*.svg
# Drug graphs: 106
generate_rategraphs:
run: stata-mp:latest analysis/106_cr_graphs_rates.do
needs: [generate_dataset_prepandemic, generate_dataset_pandemic, generate_dataset_postpandemic, generate_analysis_datasets, generate_rates]
outputs:
highly_sensitive:
log1: logs/106_cr_graphs_rates.log
moderately_sensitive:
Figures1: output/tabfig/rates_*.svg
# Drug graphs: 107
generate_drugescalation23:
run: stata-mp:latest analysis/107_cr_cohorts_escalation_2_3.do
needs: [generate_dataset_escalation, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/107_cr_cohorts_escalation.log
dataset1: output/tabfig/escalation_rates_2_3_prepandemic_redacted_rounded.csv
dataset2: output/tabfig/escalation_rates_2_3_pandemic_redacted_rounded.csv
dataset3: output/tabfig/escalation_rates_2_3_postpandemic_redacted_rounded.csv
moderately_sensitive:
Figures1: output/tabfig/escalation_2_3_*.svg
# Drug graphs: 108
generate_drugescalation34:
run: stata-mp:latest analysis/108_cr_cohorts_escalation_3_4.do
needs: [generate_dataset_escalation, generate_analysis_datasets]
outputs:
highly_sensitive:
log1: logs/107_cr_cohorts_escalation_3_4.log
dataset1: output/tabfig/escalation_rates_3_4_prepandemic_redacted_rounded.csv
dataset2: output/tabfig/escalation_rates_3_4_pandemic_redacted_rounded.csv
dataset3: output/tabfig/escalation_rates_3_4_postpandemic_redacted_rounded.csv
moderately_sensitive:
Figures1: output/tabfig/escalation_3_4_*.svg
# TIME SERIES
generate_dataset_timeseries:
run: ehrql:v1 generate-dataset analysis/dataset_timeseries.py --output output/dataset_timeseries.csv
outputs:
highly_sensitive:
dataset: output/dataset_timeseries.csv
# Measures
measures:
run: ehrql:v1 generate-measures analysis/measures.py
--output output/measures/measures.csv
--
--start-date "2018-01-01"
--intervals 64
outputs:
highly_sensitive:
measure_csv: output/measures/measures.csv
# Time series do file
run_timeseries:
run: stata-mp:latest analysis/109_time_series.do --dummy-data-file measures_dummy.csv
needs: [generate_dataset_timeseries, measures]
outputs:
highly_sensitive:
log1: logs/time_series.log
dataset: output/tabfig/measures_redacted_rounded.csv
moderately_sensitive:
Figures1: output/tabfig/time_series_*.svg
Timeline
-
Created:
-
Started:
-
Finished:
-
Runtime: 00:00:10
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Job information
- Status
-
Failed
- Backend
- TPP
- Workspace
- covid_collateral_hf_update
- Requested by
- Emily Herrett
- Branch
- main
- Force run dependencies
- No
- Git commit hash
- 623c241
- Requested actions
-
-
generate_drugprevalence_duration
-
Code comparison
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