Job request: 2866
- Organisation:
- The London School of Hygiene & Tropical Medicine
- Workspace:
- carehomes
- ID:
- dec6rwf2c4zve7f2
This page shows the technical details of what happened when the authorised researcher Emily Nightingale requested one or more actions to be run against real patient data within a secure environment.
By cross-referencing the list of jobs with the pipeline section below, you can infer what security level the outputs were written to.
The output security levels are:
-
highly_sensitive
- Researchers can never directly view these outputs
- Researchers can only request code is run against them
-
moderately_sensitive
- Can be viewed by an approved researcher by logging into a highly secure environment
- These are the only outputs that can be requested for public release via a controlled output review service.
Jobs
-
- Job identifier:
-
4wblxgtizhah72ds
-
- Job identifier:
-
igghfjsrxphvwqc3
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- Job identifier:
-
lktevfsovhyqvebd
Pipeline
Show project.yaml
version: '3.0'
expectations:
population_size: 1000000
actions:
generate_study_population:
run: cohortextractor:latest generate_cohort --study-definition study_definition
outputs:
highly_sensitive:
cohort: input.csv
check_hhid:
needs: [generate_study_population]
run: r:latest analysis/check_hhid.R input.csv
outputs:
moderately_sensitive:
log: check_hhid.txt
calc_coverage:
needs: [generate_study_population]
# last argument relates to MSOA TPP coverage >= X%
run: r:latest analysis/calculate_tpp_coverage.R input.csv data/SAPE22DT15_mid_2019_msoa.csv 80
outputs:
moderately_sensitive:
log: coverage_log.txt
rds: tpp_coverage_included.rds
rds2: tpp_coverage_all.rds
csv: tpp_coverage_all.csv
csv2: msoas_in_tpp.csv
csv3: msoa_gt_100_cov.csv
figure: total_vs_tpp_pop.png
figure2: tpp_cov_filtered.png
data_clean:
needs: [generate_study_population, calc_coverage]
# last argument relates to MSOA TPP coverage >= X%
run: r:latest analysis/data_clean.R input.csv tpp_coverage_included.rds 80
outputs:
moderately_sensitive:
log: data_clean_log.txt
highly_sensitive:
input_clean: input_clean.rds
data_check:
needs: [data_clean]
run: r:latest analysis/data_check.R input_clean.rds
outputs:
moderately_sensitive:
log: data_check_log.txt
data_check_figs:
needs: [data_clean]
run: r:latest analysis/data_check_figs.R input_clean.rds data/msoa_shp.rds
outputs:
moderately_sensitive:
figure1: tpp_coverage_msoa.png
figure2: tpp_coverage_carehomes.png
figure3: tpp_coverage_map.pdf
figure4: age_dist.png
figure5: infection_death_delays.png
figure6: hh_size_dist.png
data_setup:
needs: [data_clean]
# last argument relates to carehome TPP coverage >= X%
run: r:latest analysis/data_setup.R input_clean.rds data/cases_rolling_nation.csv 90
outputs:
moderately_sensitive:
log: data_setup_log.txt
figure: carehome_size.png
highly_sensitive:
comm_prev: community_incidence.rds
analysisdata: analysisdata.rds
ch_linelist: ch_linelist.rds
ch_agg_long: ch_agg_long.rds
descriptive:
needs: [data_clean, data_setup]
run: r:latest analysis/descriptive.R
outputs:
moderately_sensitive:
# report: descriptive.pdf
log: log_descriptive.txt
data: ch_gp_permsoa.csv
table: ch_chars_tab.csv
figure1: ch_survival.png
figure2: ch_survival_bytype.png
figure3: first_event_type.png
figure4: community_inc.png
figure5: comm_vs_ch_risk.png
figure6: comm_vs_ch_risk_log2.png
figure7: compare_epidemics.png
run_models:
needs: [data_setup]
run: r:latest analysis/run_models.R analysisdata.rds 0.0
outputs:
moderately_sensitive:
output: output_model_run.txt
log: log_model_run.txt
coeffs: coeffs_all.rds
figure: model_coeffs.pdf
table: model_comp.csv
highly_sensitive:
fit: model_out.rds
test: testdata.rds
make_table:
needs: [run_models]
run: r:latest analysis/make_coeff_table.R coeffs_all.rds
outputs:
moderately_sensitive:
table1: coeffs_table.csv
table2: coeffs_table_all.csv
# compare_models:
# needs: [run_models]
# run: r:latest analysis/compare_models.R model_out.rds
# outputs:
# moderately_sensitive:
# log: output_model_comp.txt
# coeffs: coeffs_all.rds
# figure: model_coeffs.pdf
# table: model_comp.csv
# validate_models:
# needs: [run_models]
# run: r:latest analysis/validate_models.R fits.rds testdata.rds
# outputs:
# moderately_sensitive:
# output: output_model_val.txt
# report: test_pred_figs.pdf
run_all:
needs: [run_models, descriptive]
# In order to be valid this action needs to define a run commmand and
# some output. We don't really care what these are but the below seems to
# do the trick.
run: cohortextractor:latest --version
outputs:
moderately_sensitive:
whatever: project.yaml
Timeline
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Created:
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Started:
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Finished:
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Runtime: 00:35:16
These timestamps are generated and stored using the UTC timezone on the TPP backend.
Code comparison
Compare the code used in this job request