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Danny Friel

FCSM Research & Policy Conference

October 26, 2023

Refining disclosure controls for the Census 

of Fatal Occupational Injuries (CFOI)
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Co-authors

„ Alyssa Gillen

„ Julie Krautter

„ Yvan Saastamoinen

The views expressed here are those of the authors and do not 

necessarily reflect the views or policies of the Bureau of Labor 

Statistics or any other agency of the U.S. Department of Labor.
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Road map

 What is disclosure control?

 Disclosure control for CFOI

„ Primary and secondary suppressions

„ Hypercube method

 Proposed refinements to the hypercube

 Discussion
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 The direct or indirect release of 

sensitive or private information about 

a survey or census unit

 Data users have access to other 

information

 Goal: minimize practical risk

Disclosure control
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Disclosure control

 Commonly used methods include:

„ Threshold rules

„ Dominance rules

„ Noise

 When a cell fails one or more rules, it is suppressed
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Census of Fatal Occupational Injuries (CFOI)

 Publishes a complete count of fatal injuries each year

 Protecting CFOI data is challenging

„ No sampling

„ Fatal injuries are rare events

„ Exact counts are important

„ Sixteen grouping variables for cells (industry, occupation, gender, ...)
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Primary suppression

 When disclosure rules are violated, we suppress the cell

No suppressions

Occupation Number of fatal injuries

All occupations 100

Occupation 1 80

Occupation 2 18

Occupation 3 2

Sensitive cell is suppressed

Occupation Number of fatal injuries

All occupations 100

Occupation 1 80

Occupation 2 18

Occupation 3 --
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The limits of primary suppression

Aliexpress.com Alamy.com
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Primary vs. secondary suppression

Primary suppression only

The count for occupation 3 doesn’t meet publishability criteria

Occupation Number of fatal injuries

All occupations 100

Occupation 1 80

Occupation 2 18

Occupation 3 --

Even though this cell is 

suppressed, we have enough 

information to compute its value:

100 – 80 – 18 = 2

Primary and secondary suppressions

The count for occupation 2 is suppressed as well

Occupation Number of fatal injuries

All occupations 100

Occupation 1 80

Occupation 2 --

Occupation 3 --

With two cells suppressed, we 

don’t have enough information to 

compute either value. 

Possible values include 20 and 0, 

19 and 1, 10 and 10, 15 and 5...
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Table differencing

Occupation 2 Number of fatal injuries

Full-time 12

Part-time 6
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Occupation Number of fatal injuries

1 80

2 --

3 --

Total 100

Table differencing

Occupation 2 Number of fatal injuries

Full-time 12

Part-time 6
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The CFOI Hypercube

 Scans for:

„ Primary suppressions

„ Secondary suppressions (within-tables)

„ Secondary suppressions (across tables) for up to four CFOI variables

CFOI variables Number of 

variables

Number of cells screened by 

hypercube

Fatal injuries by industry 1 706

Fatal injuries by industry, event/exposure 2 706 x 8 = 5,648

Fatal injuries by industry, event/exposure, state 3 706 x 8 x 56 = 316,288

Fatal injuries by industry, event/exposure, state, age 4 706 x 8 x 56 x 9 = 2,846,592
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Improving the hypercube

 Tradeoff:

„ Table A-1: Fatal occupational injuries by industry and event/exposure

– 5% of cells are published in 2021

 Ad-hoc improvements

 Systematic improvements

Confidentiality

Utility
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Refining the hypercube: zeroes

 Zero counts are often captured by confidentiality rules

 Zero counts are very common (80%+) in CFOI; useful for policy

 Two questions:

„ How do zero cells impact the effectiveness of secondary suppressions?

„ Can the hypercube be configured to only suppress zeroes when they 

pose a substantial confidentiality risk?
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All Events Event 1 Event 2 Event 3 Event 4 Event 5 Event 6

Industry A 21 4 -- 8 -- 4 --

Industry A-1 7 -- -- -- -- 1 --

Industry A-2 12 -- -- 3 -- 3 --

Industry A-3 2 -- -- -- -- -- --

All Events Event 1 Event 2 Event 3 Event 4 Event 5 Event 6

Industry A 21 4 -- 8 0 4 --

Industry A-1 7 -- -- -- 0 1 --

Industry A-2 12 -- -- 3 0 3 --

Industry A-3 2 0 0 -- 0 0 0

All Events Event 1 Event 2 Event 3 Event 4 Event 5 Event 6

Industry A 21 4 -- 8 0 4 --

Industry A-1 7 -- -- -- 0 1 --

Industry A-2 12 -- -- 3 0 3 --

Industry A-3 2 -- 0 -- 0 0 --

Adding zeroes to a data table (simulated data)
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Preliminary results

 Over 80% of zeroes may be publishable.

„ Zeroes must not be published if:

– They can be used to derive the value of a suppressed nonzero cell

„ Zeroes may be published if:

– They are the child of a non-zero cell or a suppressed zero cell

„ Zeroes can also be suppressed at random, to infuse more uncertainty

– E.g., if there are > 3 zeroes in a table row, up to 2 may be randomly suppressed
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Industry N, by 

event/exposure

Current 

methodology

Suppress all 

but one Suppress half Suppress two 

child cells

All events/exposures — — — —

Violence — — 11 11

Transportation — — — —

Fires and explosions — 35 35 35

Falls, slips, trips — — 16 16

Exposure to substances — — — 6

Contact with equipment — — — —

Industry Number of fatal 

injuries

K 44

L 12

M 31

N —

Proposal 2: Limiting child suppressions

Industry A, 

Occupation B

Industry A, 

Occupation B, 

State of Alabama

Industry A, 

Occupation B, 

transportation 

incidents

Industry A, 

Occupation B, 

age 35-44
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Summary

 Zero-count cells and child cells must be displayed selectively

„ Zeroes and child cells can be used to derive sensitive information

„ Cells that are non-sensitive in one table may be sensitive in another

„ Additional uncertainty can be infused as needed

 Post-processing time and resources may limit options
Contact Information

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Danny Friel

Office of Compensation and Working Conditions

Friel.Daniel@bls.gov