Group Life COVID-19 Mortality
Survey Report
MAY | 2023

Group Life COVID-19 Mortality Survey
ReportAUTHORS

Patrick Hurley, FSA, MAAA
Mike Krohn, FSA, CERA, MAAA
Tony LaSala, FSA, MAAA
Rick Leavitt, ASA, MAAA
Cynthia S. MacDonald, FSA, MAAA, SOA
Patrick Nolan, FSA, MAAA, SOA
Steve Rulis, FSA, MAAA
Matthew Sawyer, FSA, MAAASPONSORS

Group Life Experience Committee

Caveat and Disclaimer
The opinions expressed and conclusions reached by the authors are their own and do not represent any official position or opinion of the Society ofActuaries Research Institute, Society of Actuaries, or its members. The Society of Actuaries Research Institute makes no representation or warranty to theaccuracy of the information.
Copyright © 2023 by the Society of Actuaries Research Institute. All rights reserved.

3

CONTENTS
Section 1: Purpose of the Survey ............................................................................................................................... 5
Section 2: Overview .................................................................................................................................................. 6
2.1 Background .............................................................................................................................................................. 6
2.2 Scope ........................................................................................................................................................................ 6
2.3 Survey Highlights ..................................................................................................................................................... 7
Section 3: Group Life Mortality Results—Reported Death Claims ............................................................................ 11
3.1 Reported Claim Incidence by Count—All Causes ................................................................................................. 11
3.2 Reported Claim Incidence by Count—COVID-19 Versus All Other Causes ......................................................... 12
3.3 Reported Claim Incidence by Amount—All Causes ............................................................................................. 14
3.4 Reported Claim Incidence by Amount—COVID-19 Versus All Other Causes ..................................................... 14
Section 4: Group Life Mortality Results—Estimated Incurred Death Claims ............................................................. 15
4.1 Incurred Claim Incidence by Count—All Causes .................................................................................................. 15
4.2 Incurred Claim Incidence by Count—COVID-19 Versus All Other Causes .......................................................... 16
4.3 Incurred Claim incidence by Amount—All Causes ............................................................................................... 18
4.4 Incurred Claim Incidence by Amount—COVID-19 Versus All Other Causes ....................................................... 18
Section 5: Estimated Incurred Mortality Results by Segment .................................................................................. 19
5.1 Industry .................................................................................................................................................................. 20
5.2 Geography .............................................................................................................................................................. 21
5.3 Age and Sex ............................................................................................................................................................ 22
5.4 Company Size ......................................................................................................................................................... 25
Section 6: Detailed Cause of Death ......................................................................................................................... 26
Section 7: Exposure Trends ..................................................................................................................................... 30
7.1 Premiums ............................................................................................................................................................... 30
7.2 Lives ........................................................................................................................................................................ 31
Section 8: Company Variations ............................................................................................................................... 33
8.1 Variations in COVID-19 Mortality Results ............................................................................................................. 33
8.2 Variations in COVID-19 Claim Coding Procedures ............................................................................................... 34
8.3 Variations in Claim Reporting Patterns................................................................................................................. 34
Section 9: Comparisons to General U.S. Population Mortality Results ..................................................................... 35
9.1 Aggregate Excess Mortality Comparisons ............................................................................................................ 35
9.2 Excess Mortality Comparison by Sex and Age ...................................................................................................... 36
9.3 Excess Mortality Comparison by Geographic Region .......................................................................................... 47
9.4 Excess Mortality Comparison by Vaccination Uptake ......................................................................................... 49
Section 11: List of Participating Companies ............................................................................................................. 58
Appendix A: 2020 SOA Group Term Life COVID-19 Mortality Survey Data Request ................................................. 59
Appendix B: Geography and Industry Code Mappings ............................................................................................. 62
Appendix C: Survey Methodology and Documentation ........................................................................................... 67
C.1 Documentation ...................................................................................................................................................... 67
C.2 Results Processing and Review ............................................................................................................................. 69
C.2.1 Completion of Claims ............................................................................................................................. 69
C.2.2 Broader Classification of Segment Information ................................................................................... 69
C.2.3 Unknown Claim Diagnosis ..................................................................................................................... 69
C.2.4 COVID-19 Claims from 2019 or Earlier ................................................................................................. 69

Copyright © 2023 Society of Actuaries Research Institute4

C.2.5 Groupings by Company Size .................................................................................................................. 69
Appendix D: Completion Factor Development ........................................................................................................ 71
D.1 By Claim Count ...................................................................................................................................................... 71
D.2 By Face Amount..................................................................................................................................................... 73
D.3 By Cause of Death ................................................................................................................................................. 73
D.4 By Company Reporting Speed .............................................................................................................................. 74
Appendix E: Cause of Death Mapping ..................................................................................................................... 75
About The Society of Actuaries Research Institute .................................................................................................. 76

Copyright © 2023 Society of Actuaries Research Institute5Group Life COVID-19 Mortality Survey Report
Section 1: Purpose of the Survey
The purpose of this survey was to gather a high-level view of U.S. Group Term Life Insurance mortality results during
the COVID-19 pandemic, as compared to prior period baseline mortality results. COVID-19 is caused by the novel
coronavirus SARS-CoV-2, which was identified in 2019. As of the writing of this document, complications fromCOVID-19 have resulted in more than 1.1 million deaths in the U.S. alone, and more than 6.8 million worldwide.
This report is an update to the previous Group Life COVID-19 Mortality Survey published in November 2022, which
included pandemic data from April 2020 through June 2022. This update includes Group Life mortality results from
April 2020 through December 2022 (referred to in this report as the “pandemic period”), representing 33 months ofGroup Life mortality experience during the COVID-19 pandemic.
The survey was conducted by the Group Life Experience Committee (the Committee) of the Society of Actuaries andhas been structured as a recurring monthly data collection and compilation process from U.S. Group Term Life
insurers. The datasets for this report encompass all Group Term Life claims for the calendar years 2017–2022
reported to participating carriers as of December 31, 2022, and include more than 2.7 million claims and more than$120 billion in earned premium. The Committee is grateful that 20 of the top 21 U.S. Group Term Life insurers
focused on employer groups are participating in this survey, with market share representing roughly 90% of theemployer-based Group Term Life industry. Thus, the Committee believes the findings herein are representative of
the COVID-19 mortality impact on the U.S. Group Term Life industry as a whole.
Guiding principles for the survey include the following:•••

Providing timely information on total high-level Group Life mortality results versus baseline expectations
during the pandemic is the most important goal. Thus, the survey is not a seriatim mortality study. Rather,
it is a synopsis of monthly Group Life exposures, death counts and amounts.
It is critical for this survey to compare current Group Life mortality from all causes of death to the baseline
expected all-cause mortality levels. The Committee recognizes the existence of limitations in the ability tocode deaths as COVID-19 related, within both the general population and Group Life exposures. Also, thesurvey seeks to analyze whether the pandemic has had indirect impacts on population mortality, beyond
deaths associated directly with the COVID-19 virus. Thus, tracking just Group Life deaths coded with acause of COVID-19 may not accurately measure the total impact of the pandemic.
The Committee asked carriers to provide segmentation data when feasible. However, the Committee did
not want the additional detailed data request to become so onerous that it materially delayed the survey
reporting process or shrank the number of carriers willing and able to participate. Thus, the survey includes
high-level exposure and claims data for all 20 carriers, but many of the segmentation data are based on
results for just subsets of carriers.

Copyright © 2023 Society of Actuaries Research Institute6

Section 2: Overview
2.1 BACKGROUND
Carriers provided a complete set of monthly Group Life exposures dating back to January 2017, along with all Group
Life death claims reported in January 2017 or later. The reported death claims also identified the months of death,that is, incurred months.
Exposures and deaths during the three-year period of 2017–2019 were used to set baseline mortality expectations.
The dataset for this report encompasses all Group Life claims reported to participating carriers as of December 31,
2022. Reported claims are easier to measure than incurred claims, but they do not tell the full story about Group
Life mortality through December 2022 because the reported claims in a given month include deaths from priorperiods. Therefore, claim reporting patterns from prior periods have been analyzed to develop completion factors,
which are used to estimate incurred but not yet reported claims for each month. This enabled the Committee toestimate incurred claims for each month up through December 2022.
As in prior reports, the most recent one-to-two incurral months should not be fully relied upon because of thematurity of the completion of reported claims, with the completion percentages for the most recent two months
falling in the 30%–35% and 70%–75% ranges, respectively. The Committee has observed significant reporting lag
volatility over the course of the study, resulting in volatility of incurred incidence development over time, especiallyin the most recent incurred months.

2.2 SCOPE
The following specifications were used to define claims and exposures within the survey:•

Include Group Term Life only; exclude Group Whole Life, Group Universal Life, Company-Owned Life
Insurance and 10- or 20-year Group Term, etc.

•

Include both list billed and self-administered business.

•

Include employee, spouse and child exposures and deaths.

•

Include both active and retired lives and claims.

•

Include death benefits only; exclude riders, interest payments and claims expenses.

•

Include only the life insurance benefit for accidental deaths; exclude any additional Accidental Death andDismemberment rider amounts.

•

Exclude Waiver of Premium disabilities but include deaths from persons on Waiver of Premium status.

•

Portability and Conversion exposures and claims may be either included or excluded based on eachcompany’s internal reporting procedures.

Copyright © 2023 Society of Actuaries Research Institute7

2.3 SURVEY HIGHLIGHTS
Tables 2.1 through 2.41 display high-level incidence results for the second quarter of 2020 through the fourth
quarter of 2022 compared to the 2017–2019 baseline period for each combination of (a) incurred/reported basisand (b) count/amount basis as of December 31, 2022. In these tables, the number of COVID-19 claims has not beenadjusted for seasonality, but the ratios to baseline have been adjusted for seasonality.
Table 2.1

COUNT-BASED INCURRED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE
Q2 2020–
Count-Based2021
Q1 2022 Q2 2022 Q3 2022 Q4 2022
Q4 2020
Total/Baseline
119.5%
121.8%
116.5%
98.6%
102.7%
105.0%
COVID-19 Claims
45,702
77,382
19,031
2,167
3,117
1,891

105.7%
26,205

Q2 2020–
Q4 2022115.2%
149,290

COVID/Baseline

14.4%

18.2%

16.6%

2.0%

3.0%

1.7%

5.8%

12.6%

Non-COVID/Baseline

105.1%

103.6%

99.9%

96.6%

99.7%

103.3%

99.9%

102.6%

2022

Table 2.2

AMOUNT-BASED INCURRED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE (CLAIMS IN MILLIONS)
Q2 2020–
Q2 2020–
Amount-Based2021
Q1 2022 Q2 2022 Q3 2022 Q4 2022
2022
Q4 2020
Q4 2022
Total/Baseline
125.8%
139.8%
128.6%
111.5%
117.7%
118.7%
119.1%
128.4%
COVID-19 Claims
1,691
3,954
842
73
105
56
1,077
6,723
COVID/Baseline

14.6%

25.6%

20.1%

1.9%

2.8%

1.4%

6.5%

15.6%

Non-COVID/Baseline

111.2%

114.2%

108.5%

109.6%

114.9%

117.3%

112.6%

112.8%

Table 2.3

COUNT-BASED REPORTED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE
Q2 2020–
Count-Based2021
Q1 2022 Q2 2022 Q3 2022 Q4 2022
Q4 2020
Total/Baseline
115.6%
123.6%
123.0%
102.3%
106.5%
102.5%
COVID-19 Claims
33,79980,15522,869
5,103
3,558
2,257

108.6%
33,787

Q2 2020–
Q4 2022115.9%
147,741

COVID/Baseline

11.0%

19.0%

19.7%

4.6%

3.4%

2.2%

7.5%

12.6%

Non-COVID/Baseline

104.6%

104.6%

103.3%

97.7%

103.1%

100.3%

101.1%

103.3%

2022

Table 2.4

AMOUNT-BASED REPORTED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE (CLAIMS IN MILLIONS)
Q2 2020–
Q2 2020–
Amount-Based2021
Q1 2022 Q2 2022 Q3 2022 Q4 2022
2022
Q4 2020
Q4 2022
Total/Baseline
124.0%
140.7%
137.7%
111.3%
120.9%
114.3%
121.0%
128.9%
COVID-19 Claims
1,345
3,936
1,058
175
119
64
1,416
6,696
COVID/Baseline

12.1%

26.0%

25.2%

4.3%

3.1%

1.7%

8.6%

15.8%

Non-COVID/Baseline

111.9%

114.7%

112.5%

107.0%

117.8%

112.6%

112.4%

113.1%

1 A small number of COVID-19 claims received were dated before 2020. The Committee assumes these dates are data errors. They were not assigned to aparticular date in 2020 or later, and so these claims are excluded from Tables 2.1–2.4. They are, however, included in the total COVID claims in Section 5.

Copyright © 2023 Society of Actuaries Research Institute8Group Life carriers generally started receiving a small number of COVID-19 death claims during March 2020, but
April 2020 was the first month in which the Group Life industry saw a material number of reported COVID-19 deathclaims. This drove April 2020 Group Life reported incidence to be measurably larger than baseline expectedreported incidence. Reported incidence has remained materially higher than baseline in almost all months during
the pandemic period. The lone exceptions were May 2021, May 2022 and October 2022, during which reported
incidence was approximately 1%, 2% and 4% lower than baseline, respectively.
It is important to note that incurred estimates for the most recent months lack credibility because of the low level ofcompletion of the data used at the time of this analysis. Group Life claim completion has been especially volatile
during the pandemic waves, driven both by the ultimate incurred levels fluctuating from month to month and bycompany-specific claim-processing speeds fluctuating up and down because of increases or decreases in staffing
levels and build-up or build-down of claim backlogs.
From an incurred mortality viewpoint, 30 of the 33 months from April 2020 through December 2022 showed excess
mortality2 versus baseline expectations. The lone exceptions were March, April and October 2022, during whichmortality was 1%, 4% and 1% lower than baseline, respectively. December 2020, January 2021, August 2021 and
September 2021 each had very high incurred excess mortality spikes of 40% or more.
The 33-month period of April 2020 through December 2022 showed the following Group Life mortality results:••

Estimated reported Group Life claim incidence rates were up 15.9% on a seasonally adjusted basis
compared to 2017–2019 reported claims.
Estimated incurred Group Life incidence rates were 15.2% higher than baseline on a seasonally adjusted
basis. As noted above, the incurred incidence rates in November and December 2022 are based on fairly
incomplete data, so they are subject to change and should not be fully relied upon at this point.

Additional highlights include the following:••

Approximately 11% of all reported Group Life claims with death dates in the pandemic period were
determined to have a cause of death (COD) of COVID-19.
The Gray-Collar group had the lowest actual-to-expected ratios (A/E’s) relative to baseline over the
pandemic period at around 10%, followed by the Blue-Collar group at 14%. The White-Collar group
continues to have the highest mortality A/E relative to baseline at 19% during the pandemic period.

2For the purposes of this report, “excess mortality” refers to the percentage change in incidence rates observed during the pandemic compared to the

2017–2019 baseline period.

Copyright © 2023 Society of Actuaries Research Institute

9

•

•

•

Group Life mortality patterns by region have changed over time during the COVID-19 pandemic. The
Midwest had the highest excess mortality for the most recent quarter included in this update. The
following regions had the highest excess mortality in each quarter shown:o Q2 2020: Northeast (41%)
o Q3 2020: Southeast (27%)
o Q4 2020: Midwest (33%)
o Q1 2021: Southeast (33%)
o Q2 2021: Southeast (11%)
o Q3 2021: Southeast (62%)
o Q4 2021: Midwest (32%)
o Q1 2022: Southeast (19%)
o Q2 2022: Northeast (2%)
o Q3 2022: Southeast (6%)
o Q4 2022: Midwest (14%)
Starting with the June 2022 data submission, companies began supplying much more granular COD data.
Initial findings show incurred mortality increases in several causes during the pandemic period, including
cardiovascular, liver, diabetes and drug overdoses. Cancer and influenza/pneumonia incurred mortality
levels have been down during the pandemic period as compared to baseline. Additional details are shownin Section 6.
Early quarters of the pandemic period (Q2 and Q3 2020) showed the Group Life insured population studied
within this survey experienced a lower percentage of excess deaths than the U.S. population, as shown in
Table 2.5. Each quarter in 2021 showed higher excess mortality in the U.S. population than the Group Life
population. However, in 2022, this comparison reversed, and the Group Life has shown lower excess
mortality than the U.S. population in the most recent three quarters.
Table 2.5

GROUP LIFE AND U.S. POPULATION EXCESS MORTALITY PERCENTAGES BY QUARTER

Group Life

Q2
2020
15%

Q3
2020
15%

Q4
2020
28%

Q1
2021
22%

Q2
2021
7%

Q3
2021
33%

Q4
2021
25%

Q1
2022
16%

Q2
2022
-1%

Q3
2022
3%

Q4
2022
5%

U.S. Population

20%

16%

26%

16%

5%

24%

18%

15%

2%

7%

7%

Difference

-5%

-1%

2%

6%

2%

9%

7%

1%

-3%

-4%

-2%

Age

•

•

In the third quarter of 2021, a moderate negative correlation was seen between vaccination rate andexcess mortality by state. However, this correlation has considerably weakened in subsequent periods.
Other factors potentially influencing this relationship are climate, seasonality, preventative measures (e.g.,social distancing and masking), deaths from causes other than COVID-19, varying degrees of vaccine
effectiveness against different variants of the virus, and a higher degree of natural immunity due to past
infections in the later period. This is explained in further detail in Section 9.5.
Section 9 includes a comparison of proportional excess deaths in the Group Life market to the U.S.
population, segmented by sex and age and cause of death. This feature was not present in previous
iterations of this report. Overall, the experience between the two populations was quite similar, but inseveral instances the experience differs:ooFor the older ages (over age 65) the Group Life mortality has improved in 2022 relative to 2020–2021
significantly more than in the U.S. population.
Group Life mortality for major cardiovascular disease has also improved in 2022 relative to 2020–2021
more than in the U.S. population.

Copyright © 2023 Society of Actuaries Research Institute

10

o
o

More improvement relative to 2020–2021 was observed in cancer morality within the Group Lifemarket than in the U.S. population, but the improvement extends over the entire pandemic period.
The proportional impact of death due to liver disease was much higher within the total U.S. population
than within the Group Life market through the entire pandemic period.

Copyright © 2023 Society of Actuaries Research Institute11

Section 3: Group Life Mortality Results—Reported Death Claims
3.1 REPORTED CLAIM INCIDENCE BY COUNT—ALL CAUSES
On a seasonally adjusted basis, Q4 2022 reported incidence by count was 102.5% of baseline levels, with October
2022 being 3.8% below baseline and November and December being both above baseline.
Reported overall Group Life claim incidence rates during the pandemic period, as shown in Figure 3.1, are up
approximately 16% compared to 2017–2019 reported claims. Reported claims are easier to measure than incurredbecause no estimation of completeness is required. However, reported claims do not explain the true economic
impact of what is happening in the claim experience of a particular reported period because those reported claims
include deaths associated with prior periods, which may or may not have been accurately expected and accrued inprior period claim liabilities.
Figure 3.1

AGGREGATE REPORTED CLAIM INCIDENCE PER 1,000 BY CALENDAR YEAR AND MONTH
4.80
4.40
4.00
3.60
3.20
2.80
2.40
Jan.

Feb.
2017

Mar.

Apr.
2018

May.

June
2019

July

Aug.
2020

Sep.

Oct.
2021

Nov.

Dec.
2022

Note: Incidence rates in Figure 3.1 have not been adjusted for seasonality.
Figure 3.2 is a different view of the data displayed in Figure 3.1 to illustrate the flow of excess reported mortality
over the entire pandemic period.

Copyright © 2023 Society of Actuaries Research Institute

12Figure 3.2

AGGREGATE REPORTED CLAIM INCIDENCE PER 1,000 BY CALENDAR MONTH
4.80
4.40
4.00
3.60
3.20
2.80

Dec-22Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Dec-20Mar-21

Jun-20

Sep-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-16

2.40

12 Month Moving Average

Note: Incidence rates in Figure 3.2 have not been adjusted for seasonality.

3.2 REPORTED CLAIM INCIDENCE BY COUNT—COVID-19 VERSUS ALL OTHER CAUSES
A total of 147,741 COVID-19 death claims were reported during the pandemic period. Roughly 74% of the COVID-19
claims were for Basic Group Life coverage and roughly 26% for Supplemental/Voluntary coverage, with both figures
including active employees and retirees. Note that the exposures and claim counts for insureds with both Basic andSupplemental/Voluntary coverage were included in both product lines. Thus, some deaths were counted as both
Basic and Supplemental/Voluntary deaths, so the total number of Group Life insureds with COVID-19 deaths is lessthan 147,741.
Table 3.1 shows the total death claim incidence level (mortality rate) for each quarter during the pandemic relative
to the baseline period metric. The table also shows a relativity for COVID-19 claims and non-COVID claims. As thetable illustrates, COVID-19 claims do not fully explain the increase in reported claim incidence over the baseline
period.
Table 3.1

COUNT-BASED REPORTED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE
Q2 2020–
Count-Based2021
Q1 2022 Q2 2022 Q3 2022 Q4 2022
Q4 2020
Total/Baseline
115.6%
123.6%
123.0%
102.3%
106.5%
102.5%
COVID-19 Claims
33,79980,15522,869
5,103
3,558
2,257

108.6%
33,787

Q2 2020–
Q4 2022115.9%
147,741

COVID/Baseline

11.0%

19.0%

19.7%

4.6%

3.4%

2.2%

7.5%

12.6%

Non-COVID/Baseline

104.6%

104.6%

103.3%

97.7%

103.1%

100.3%

101.1%

103.3%

2022

Copyright © 2023 Society of Actuaries Research Institute13

Reported claim details by month are shown in Table 3.2, along with calculated monthly reported incidence rates.
Note that a small number of COVID-19 claims have reported dates of death in 2019 or prior, which are likely due todata errors.
Table 3.2

REPORTED CLAIMS AND INCIDENCE RATES, 2017 THROUGH Q4 2022
Report Date

12/1/22
11/1/22
10/1/22
9/1/22
8/1/22
7/1/22
6/1/22
5/1/22
4/1/22
3/1/22
2/1/22
1/1/22
12/1/21
11/1/21
10/1/21
9/1/21
8/1/21
7/1/21
6/1/21
5/1/21
4/1/21
3/1/212/1/21
1/1/21
12/1/20
11/1/20
10/1/20
9/1/208/1/207/1/206/1/205/1/204/1/203/1/202/1/201/1/202017–2019Baseline
2019 Monthly
2018 Monthly
2017 Monthly

Raw Submitted Numbers
Reported Claims
Premium($ 000)Total
COVID
34,699564
1,808,601
35,288808
1,768,521
34,592885
1,802,898
35,895
1,101
1,812,394
39,425
1,286
1,805,362
35,9391,171
1,815,764
37,671
1,217
1,811,223
37,152
1,523
1,814,863
37,7642,363
1,817,438
49,4876,024
1,807,962
46,2598,321
1,806,888
47,7718,524
1,803,089
44,441
6,925
1,764,082
41,5786,949
1,706,630
44,1939,437
1,719,315
47,177
10,004 1,708,856
41,655
4,816
1,702,905
36,4701,818
1,722,550
40,0442,723
1,727,118
36,7183,487
1,736,159
41,631
4,872
1,739,930
50,717
8,077
1,729,518
47,507
10,201 1,722,700
48,371
10,846 1,718,064
46,5417,884
1,686,456
36,657
3,628
1,666,391
38,703
2,753
1,668,879
38,6893,108
1,672,493
38,245
3,384
1,674,390
39,6402,899
1,693,214
39,5403,124
1,685,726
38,675
3,953
1,739,235
40,853
3,066
1,696,977
37,831150
1,699,364
36,434
3
1,726,142
39,3694
1,683,276
34,6630
1,592,974

Life Years Exposed(000)
By Month
Yrly Avg
11,252
11,171
10,976
11,171
11,157
11,171
11,191
11,171
11,189
11,171
11,158
11,171
11,229
11,171
11,198
11,171
11,251
11,171
11,116
11,171
11,189
11,171
11,148
11,171
11,201
10,871
10,782
10,871
10,817
10,871
10,74910,871
10,815
10,871
10,792
10,871
10,893
10,871
10,893
10,871
10,91910,871
10,877
10,871
10,872
10,871
10,836
10,871
10,944
10,96910,861
10,96910,776
10,96910,853
10,96910,893
10,96910,968
10,96910,963
10,969
11,202
10,96910,90010,96910,978
10,96911,304
10,96910,984
10,96910,717
10,71735,50034,742
33,747

10,888
10,688
10,57511
01,647,707
1,589,360
1,541,855

10,888
10,688
10,575

Calculated Amounts
Annual Incidence
Adjusted for Seasonality
per 1,000(Lives Basis)
Total
Total/Baseline
3.11
3.35
103.5%
3.16
3.49
107.8%
3.10
3.11
96.2%
3.21
3.55
109.7%
3.53
3.43
105.9%
3.22
3.36
103.9%
3.37
3.47
107.4%
3.33
3.16
97.7%
3.38
3.30
101.8%
4.43
3.96
122.3%
4.14
4.06
125.6%
4.28
3.92
121.2%
4.09
4.41
136.2%
3.82
4.22
130.5%
4.07
4.09
126.3%
4.34
4.79
148.1%
3.83
3.72
115.0%
3.35
3.51
108.3%
3.68
3.80
117.3%
3.38
3.21
99.2%
3.83
3.73
115.4%
4.67
4.17
128.8%
4.37
4.29
132.5%
4.45
4.08
126.1%
4.24
4.59
141.7%
3.34
3.70
114.4%
3.53
3.56
109.9%
3.53
3.91
120.7%
3.49
3.40
104.9%
3.61
3.79
117.0%
3.60
3.72
115.1%
3.53
3.36
103.9%
3.72
3.64
112.5%
3.45
3.09
95.5%
3.32
3.16
97.5%
3.59
3.30
102.0%
3.23
3.24
100.0%
3.26
3.25
3.19

3.26
3.25
3.20

100.9%
100.4%
98.7%

Copyright © 2023 Society of Actuaries Research Institute14

3.3 REPORTED CLAIM INCIDENCE BY AMOUNT—ALL CAUSES
Reported overall Group Life claim incidence rates by amount during the pandemic period were up roughly 29%
compared to 2017–2019 reported amounts. This increase in incidence rates by amount is notably higher than thecorresponding incidence rate increase by count. The difference is likely driven by salary and face amount inflation
over the five-year period, changes in age and gender mix, and the relatively higher excess mortality being reported
at typical working ages (where face amounts are greater).

3.4 REPORTED CLAIM INCIDENCE BY AMOUNT—COVID-19 VERSUS ALL OTHER CAUSES
Table 3.3

AMOUNT-BASED REPORTED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE (CLAIMS IN MILLIONS)
Q2 2020–
Q2 2020–
Amount-Based2021
Q1 2022 Q2 2022 Q3 2022 Q4 2022
2022
Q4 2020
Q4 2022
Total/Baseline
124.0%
140.7%
137.7%
111.3%
120.9%
114.3%
121.0%
128.9%
COVID-19 Claims
1,345
3,936
1,058
175
119
64.1
1,416
6,696
COVID/Baseline

12.1%

26.0%

25.2%

4.3%

3.1%

1.7%

8.6%

15.8%

Non-COVID/Baseline

111.9%

114.7%

112.5%

107.0%

117.8%

112.6%

112.4%

113.1%

Copyright © 2023 Society of Actuaries Research Institute15

Section 4: Group Life Mortality Results—Estimated Incurred Death Claims
4.1 INCURRED CLAIM INCIDENCE BY COUNT—ALL CAUSES
A completed estimate of incurred incidence rates by count indicates that excess mortality for the pandemic period
was approximately 15% higher than the 2017–2019 baseline incurred incidence. Figure 4.1 displays the various
monthly estimated incurred incidence rates.
Figure 4.1

AGGREGATE INCURRED CLAIM INCIDENCE PER 1,000 BY CALENDAR YEAR AND MONTH
5.20
4.90
4.60
4.30
4.00
3.70
3.40
3.10
2.80
Jan.

Feb.
2017

Mar.

Apr.
2018

May.

June
2019

July

Aug.
2020

Sep.

Oct.
2021

Nov.

Dec.
2022

Note: Adjusted for assumed completion.
The initial estimates of Q4 2022 incurred incidence rates indicate that mortality was 105% of baseline on aseasonally adjusted count basis. The monthly results within Q4 show October 2022 estimated incurred mortality of
1% below baseline, whereas November and December were above baseline. The November and December results
are still highly incomplete and likely to change as more months of reported claims are revealed.
The current view of Q3 2022 results indicate excess incurred mortality of 2.7%, with all three months of the quarterwithin 1% of the overall quarterly average.
Figure 4.2 is a different view of the data displayed in Figure 4.1 to illustrate the flow of estimated excess incurredmortality over the entire pandemic period.

Copyright © 2023 Society of Actuaries Research Institute

16

Figure 4.2

AGGREGATE INCURRED CLAIM INCIDENCE PER 1,000 BY CALENDAR MONTH
5.20
4.90
4.60
4.30
4.00
3.70
3.40
3.10
Dec-22Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Dec-20Mar-21

Jun-20

Sep-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-162.80

12 per. Mov. Avg. (Incurred Incidence)

Note: Adjusted for assumed completion. Incidence rates in Figure 4.2 have not been adjusted for seasonality.

4.2 INCURRED CLAIM INCIDENCE BY COUNT—COVID-19 VERSUS ALL OTHER CAUSES
Similar to reported claim metrics, Table 4.1 shows that COVID-19 claims do not fully explain the increase in incurredclaim incidence on a count basis. COVID-19 claims account for roughly 83% of the excess incurred Group Lifemortality during the second quarter of 2020 through the fourth quarter of 2022, with the other 17% coming fromclaims that were not coded with COVID-19 as cause of death.
Table 4.1

INCURRED EXCESS MORTALITY BY CLAIM COUNT COMPARED TO 2017–2019 BASELINE
Q2 2020–
Count-Based2021
Q1 2022 Q2 2022 Q3 2022 Q4 2022
Q4 2020
Total/Baseline
119.5%
121.8%
116.5%
98.6%
102.7%
105.0%
COVID-19 Claims
45,702
77,382
19,031
2,167
3,117
1,891

2022
105.7%
26,205

Q2 2020–
Q4 2022115.2%
149,290

COVID/Baseline

14.4%

18.2%

16.6%

2.0%

3.0%

1.7%

5.8%

12.6%

Non-COVID/Baseline

105.1%

103.6%

99.9%

96.6%

99.7%

103.3%

99.9%

102.6%

Incurred claim details by month are shown in Table 4.2, along with calculated monthly incurred incidence rates.
Note that a small number of COVID-19 claims have incurred dates of death in 2019 or prior, which are likely due todata errors.

Copyright © 2023 Society of Actuaries Research Institute17

Table 4.2

INCURRED CLAIM COUNTS AND INCIDENCE RATES, 2017 THROUGH Q4 2022
Incurral Date

12/1/22
11/1/22
10/1/22
9/1/22
8/1/22
7/1/22
6/1/22
5/1/22
4/1/22
3/1/22
2/1/22
1/1/22
12/1/21
11/1/21
10/1/21
9/1/21
8/1/21
7/1/21
6/1/21
5/1/21
4/1/21
3/1/212/1/21
1/1/21
12/1/20
11/1/20
10/1/20
9/1/208/1/207/1/206/1/205/1/204/1/203/1/202/1/201/1/202017–2019Baseline
2019 Monthly
2018 Monthly
2017 Monthly

Raw Submitted Numbers
Average Incurred
Average
Claim Counts
Premium($ 000)
Total
COVID
11,43425,17030,594
31,67933,48034,67933,291
34,66933,306
36,69040,021
52,84346,48541,98944,27048,38846,94136,873
34,84037,20137,04539,32341,06154,29953,30743,75639,30936,54939,78040,07736,032
39,41044,58538,60835,312
38,42834,724

141
421
605
764
1,074
1,068
837
683
568
1,610
5,847
11,139
7,851
5,611
7,733
12,416
9,882
1,925
1,336
2,447
3,009
3,272
6,668
14,247
13,040
7,040
3,039
2,349
3,627
3,676
1,926
3,812
6,958
1,057
22
63
2

1,808,601
1,768,521
1,802,898
1,812,394
1,805,362
1,815,764
1,811,223
1,814,863
1,817,438
1,807,962
1,806,888
1,803,089
1,764,082
1,706,630
1,719,315
1,708,856
1,702,905
1,722,550
1,727,118
1,736,159
1,739,930
1,729,518
1,722,700
1,718,064
1,686,456
1,666,391
1,668,879
1,672,493
1,674,390
1,693,214
1,685,726
1,739,235
1,696,977
1,699,364
1,726,142
1,683,276
1,592,974

Average
Life Years
Exposed(000)
11,252
10,976
11,157
11,191
11,18911,158
11,229
11,198
11,251
11,116
11,189
11,148
11,201
10,782
10,817
10,74910,815
10,792
10,893
10,893
10,91910,877
10,872
10,836
10,944
10,861
10,776
10,853
10,893
10,968
10,963
11,202
10,90010,97811,304
10,984
10,71734,86434,762
34,54522
11,647,707
1,589,360
1,541,855

10,888
10,688
10,575

Calculated Amounts
AverageAnnualAdjusted forCompleted
Incidence
Seasonality
Claim
per 1,000
Total
Total/Baseline
Counts(Lives Basis)
42,9183.81
3.60
111.0%
36,7953.35
3.41
105.1%
35,878
3.22
3.21
99.0%
34,8853.12
3.32
102.4%
35,8333.20
3.31
102.2%
36,5453.28
3.36
103.6%
34,722
3.09
3.25
100.3%
35,9263.21
3.24
100.0%
34,353
3.05
3.10
95.6%
37,706
3.39
3.20
98.8%
41,011
3.67
3.73
115.1%
54,0114.84
4.39
135.5%
47,3994.23
3.99
123.2%
42,732
3.96
4.03
124.2%
44,9864.16
4.15
128.0%
49,102
4.57
4.87
150.1%
47,5814.40
4.55
140.5%
37,337
3.46
3.55
109.4%
35,2433.24
3.40
105.0%
37,5993.45
3.49
107.6%
37,4093.43
3.48
107.3%
39,6773.65
3.44
106.3%
41,401
3.81
3.88
119.6%
54,711
5.05
4.58
141.2%
53,6744.90
4.64
143.1%
44,0294.05
4.13
127.4%
39,531
3.67
3.67
113.3%
36,737
3.39
3.61
111.5%
39,964
3.67
3.81
117.5%
40,245
3.67
3.77
116.4%
36,1693.30
3.48
107.3%
39,5403.53
3.58
110.3%
44,7174.10
4.17
128.8%
38,706
3.53
3.34
103.0%
35,389
3.13
3.09
95.2%
38,449
3.50
3.18
98.2%
34,7433.24
3.24
100.0%
34,88334,781
34,564

3.20
3.25
3.27

3.20
3.25
3.27

98.9%
100.3%
100.8%

Copyright © 2023 Society of Actuaries Research Institute18

4.3 INCURRED CLAIM INCIDENCE BY AMOUNT—ALL CAUSES
Overall, seasonally adjusted incurred Group Life claim incidence rates by amount during the pandemic period wereup roughly 28% compared to the 2017–2019 baseline. This increase in incidence rates by amount is notably higher
than the corresponding increase in incidence rates by count. The difference is likely driven by salary and face
amount inflation over the five-year period, changes in age and gender mix, and the relatively higher excess mortality
being incurred at typical working ages (where face amounts are greater).

4.4 INCURRED CLAIM INCIDENCE BY AMOUNT—COVID-19 VERSUS ALL OTHER CAUSES
Similar to Table 4.1, Table 4.3 shows that COVID-19 claims do not fully explain the increase in incurred claim
incidence on an amount basis.
Table 4.3

AMOUNT-BASED INCURRED INCIDENCE RESULTS RELATIVE TO 2017–2019 BASELINE
Q2 2020–
Amount-Based2021
Q1 2022 Q2 2022 Q3 2022 Q4 2022
Q4 2020
Total/Baseline
125.8%
139.8%
128.6%
111.5%
117.7%
118.7%
COVID-19 Claims
1,691
3,954
842
73
105
56

119.1%
1,077

Q2 2020–
Q4 2022128.4%
6,723

COVID/Baseline

14.6%

25.6%

20.1%

1.9%

2.8%

1.4%

6.5%

15.6%

Non-COVID/Baseline

111.2%

114.2%

108.5%

109.6%

114.9%

117.3%

112.6%

112.8%

2022

Copyright © 2023 Society of Actuaries Research Institute19

Section 5: Estimated Incurred Mortality Results by Segment
Analysis of results by segment will focus on claim count experience for simplicity and credibility. In general, resultsby claim amount follow similar patterns as results by claim count.
The following notes apply to the data presented in this section:
•
•

•

•

•

Claims and A/E ratios are presented on an incurred basis. The “expected” basis is the 2017–2019 baseline.
Although most companies were able to provide segment detail, some did not. Results by Company Size
reflect all companies. Results for Industry reflect approximately 97% of total company claims, results for
Geography reflect 98% of total company claims, and results by Age/Sex reflect approximately 91% of totalcompany claims. Note that these percentages are expressed relative to baseline claim counts.
The total claim counts and A/E ratios in each subsection include only the data from companies that
produced the breakout being analyzed. For example, the “All Industries” row in Table 5.2 includes only datafrom companies that were able to supply claims data by Industry. This can result in differences in the total
A/E ratios across the various tables.
The “% COVID” columns in the tables below show the monthly average COVID claims during the pandemic
period as a percentage of the average total monthly claims from the 2017–2019 baseline period. The “%
Non-COVID” column in the Age and Sex tables reflects excess mortality due to non-COVID claims.
The “% Count” columns in the tables below show the proportion of baseline claims in each segment. For
some segments, claims were submitted with “Unknown” segmentation value. The unknowns and theirratios were omitted from the tables but are included in the totals. Unknowns also tend to account for asmall percent of the total.
For formatting purposes, the information for Q2 2020 no longer appears in the charts for this section; seeprior iterations of this report for information on excess mortality in Q2 2020.

Copyright © 2023 Society of Actuaries Research Institute20

5.1 INDUSTRY
Table 5.1 displays quarterly A/E mortality ratios by industry collar. The White-Collar category has experienced ahigher A/E ratio than the Blue- and Grey-Collar industries over the entire pandemic period, and this relationship has
been relatively consistent across time. All three categories showed peak excess mortality in the third quarter of2021. Grey-Collar has had the lowest A/E ratio throughout all of 2022, including ratios below 100% for 3 consecutive
quarters.
Table 5.1

EXCESS MORTALITY BY INDUSTRY COLLAR
Industry
Collar
Blue
Gray
White
All Collarsa

Q3
2020
110%
115%
119%
115%

Q4
2020
127%
127%
129%
128%

Q1
2021
123%
117%
123%
122%

Q2
2021
107%
104%
107%
107%

Q3
2021
129%
133%
138%
134%

Q4
2021
126%
121%
126%
125%

Q1
2022
115%
107%
121%
116%

Q2
2022
97%
88%
103%
99%

Q3
2022
100%
92%
109%
103%

Q4
2022
104%
94%
110%
106%

4/2012/22
114%
110%
119%
115%

%
COVID
13.3%
13.3%
12.5%
13.0%

%
Count
40%
19%
40%
100%

a. Includes only companies that provided Industry splits; see second bullet at the beginning of Section 5.

Tables 5.2 and 5.3 show more detailed industry results for the top 10 industry segments by number of COVID claims.
These are the same top 10 industry groupings and in the same order from the prior public report. Public
Administration (White-Collar), Manufacturing–Auto, Airplanes (Blue-Collar), Misc. Services (Grey-Collar) and
Educational Services (White-Collar) have had the highest A/E ratios since April 2020. Manufacturing–Heavy, Steel(Blue-Collar) had the lowest A/E ratio of the top 10 industries. In these tables, “B," “W”, and “G” refer to Blue-Collar,
White-Collar, and Grey-Collar, respectively.
Table 5.2

EXCESS MORTALITY FOR TOP 10 INDUSTRIES BY NUMBER OF COVID CLAIMS
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Industry
2020
2020
2021
2021
2021
2021
2022
2022
W-Public Administration
120% 133% 122% 107% 146% 136% 134% 113%
B-Transport; Communication; Utilities
111% 126% 120% 103% 129% 121% 113%
98%
B-Manufacturing - Auto, Airplanes
106% 126% 130% 118% 132% 140% 129% 108%
B-Manufacturing - Heavy; Steel
104% 126% 111%96%
113% 115%
99%
85%
W-Educational Services
118% 124% 122% 106% 135% 116% 108%
97%
W-Doctors Offices
119% 122% 118% 103% 132% 113% 109%
95%
G-Manufacturing - Paper; Drugs
110% 127% 123% 106% 127% 121% 109%85%
G-Retail - Trade
106% 113% 118% 101% 137% 121% 103%
81%
G-Wholesale Trade
121% 138% 103%95%119% 115%
97%
86%
G-Misc. Service/Data Processing
122% 128% 127% 114% 153% 130% 120% 106%All Industriesa
115% 128% 122% 107% 134% 125% 116%
99%
a. Includes only companies that provided Industry splits; see second bullet at the beginning of Section 5.

Q3
2022
116%
99%
112%
86%
115%
99%
88%
90%
87%
108%
103%

Q4
2022
116%
102%
131%
82%
113%
111%
83%
96%
99%
104%
106%

4/2012/22
124%
112%
122%
102%
115%
113%
108%
107%
108%
121%
115%

Table 5.3

COVID CLAIMS FOR TOP 10 INDUSTRIES BY NUMBER OF COVID CLAIMS
4/20%
%
#
12/22
COVID Count
COVID
124%
12.2%
14%
19,867
112%
13.3%
13%
19,666
122%
13.6%
9%
13,872
102%
12.0%
9%
11,753
115%
12.4%
6%
8,997
113%
13.6%
6%
8,771
108%
12.0%
6%
8,005
107%
14.5%
4%
7,143
108%
12.5%
5%
6,497
121%
15.0%
3%
5,412
115%
13.0%
100% 146,798
All Industriesa
a. Includes only companies that provided Industry splits; see second bullet at the beginning of Section 5.
Industry
W-Public Administration
B-Transport; Communication; Utilities
B-Manufacturing - Auto, Airplanes
B-Manufacturing - Heavy; Steel
W-Educational Services
W-Doctors Offices
G-Manufacturing - Paper; Drugs
G-Retail - Trade
G-Wholesale Trade
G-Misc. Service/Data Processing

Copyright © 2023 Society of Actuaries Research Institute21

It should be noted that the high A/E ratios for Public Administration are driven by experience in the Executive,
Legislative and General Government segment (Standard Industry Classification [SIC] codes 9100–9199). This
segment does not include police and fire and represents more than 80% of recent claims in the broader Public
Administration segment.

5.2 GEOGRAPHY
Results by Geography appear to be consistent with broad population results in terms of timing of regional spikes
across the country, as shown in Table 5.4. The Southeast shows the highest overall A/E ratio since April 2020, as wellas the highest percentage of claims identified as COVID. Smaller differences are seen in A/E ratio by region in early
2022, but the fourth quarter of 2022 saw more material differences, with the West region being favorable and theMidwest being unfavorable.
Table 5.4

EXCESS MORTALITY BY GEOGRAPHIC REGION
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
2020
2020
2021
2021
2021
2021
2022
2022
2022
2022
Northeast
106%
123%
123%
108%
116%
124%
118%
102%
102%
105%
West
121%
129%
130%
105%
132%
126%
113%
100%
100%
90%
Midwest
107%
133%
108%
105%
117%
132%
117%
97%
102%
114%
Southeast
127%
129%
133%
111%
162%
123%
119%
99%
106%
105%
115%
128%
122%
107%
134%
125%
117%
99%
103%
106%
All Regionsaa. Includes only companies that provided Geography splits; see second bullet at the beginning of Section 5.
Region4/2012/22
115%
114%
113%
120%
116%

%
COVID
11.0%
12.6%
12.2%
15.5%
13.0%

%
Count
21%
15%
28%
35%
100%

A closer look at the states with the highest number of COVID claims in Tables 5.5 and 5.6 shows results that areconsistent with the regional results in Table 5.4. Three Southeast states (Georgia, Tennessee and Florida) arecontributing to the high A/E for the Southeast since April 2020. The high A/E ratios in Michigan and Illinois
contributed to the deterioration in Midwest results in the fourth quarter of 2022. Similarly, the low A/E ratio for
California is in line with the favorable West result for the quarter.
Table 5.5

EXCESS MORTALITY FOR TOP 10 STATES BY NUMBER OF COVID CLAIMS
State

Q3
2020

Q4
2020

Q1
2021

Q2
2021

Q3
2021

Q4
2021

Q1
2022

Q2
2022

Q3
2022

Q4
2022

TX - Southeast
CA - WestFL - Southeast
MI - Midwest
OH - Midwest
PA - Northeast
GA - Southeast
IL - Midwest
NY - Northeast
TN - Southeast
All Statesa

134%
125%
129%
103%
105%
106%
136%
107%
108%
122%
115%

135%
135%
117%
130%
130%
130%
131%
134%
117%
134%
128%

137%
150%
127%
109%
111%
121%
146%
108%
131%
131%
122%

104%
103%
117%
116%
100%
108%
118%
102%
108%
116%
107%

159%
129%
186%
110%
115%
114%
179%
112%
112%
159%
134%

118%
114%
118%
144%
136%
135%
133%
118%
118%
136%
125%

117%
115%
114%
115%
114%
116%
121%
116%
115%
126%
117%

97%
99%
100%
99%
89%
99%
104%
95%
100%
100%
99%

104%
100%
108%
104%
96%
101%
112%
98%
98%
111%
103%

90%
83%
104%
119%
105%
108%
114%
113%
101%
124%
106%

Apr.
2020–
Dec.
2022
118%
115%
121%
116%
110%
114%
128%
111%
116%
124%
116%

a. Includes only companies that provided Geography splits; see second bullet at the beginning of Section 5.

Copyright © 2023 Society of Actuaries Research Institute22

Table 5.6

COVID CLAIMS FOR TOP 10 STATES BY NUMBER OF COVID CLAIMSStateTX - Southeast
CA - WestFL - Southeast
MI - Midwest
OH - Midwest
GA - Southeast
PA - Northeast
IL - Midwest
NY - Northeast
TN - Southeast
All Statesa

Apr.
2020–
Dec.
2022
118%
115%
121%
116%
110%
114%
128%
111%
116%
124%
116%

COVID
(%)

Count
(%)

No.
COVID

18.6%
12.8%
13.0%
13.2%
12.9%
11.7%
16.3%
10.9%
10.2%
16.3%
13.0%

8%
6%
6%
6%
5%
5%
3%
5%
4%
3%
100%

17,429
9,285
9,135
8,535
7,219
6,573
6,331
6,277
5,200
4,830
149,417

a. Includes only companies that provided Geography splits; see second bullet at the beginning of Section 5.

5.3 AGE AND SEX
For the Age and Sex segments, excess mortality for the pandemic period was also split between COVID and nonCOVID claims. For example, for the 45–64 age group, the 18.2% COVID and 6.8% Non-COVID total 25.0% excess
mortality, which equates to the 125% A/E ratio since April 2020. The 65+ age band continues to have lower A/E
ratios than younger age bands, and all of the excess mortality for this age group (which includes retirees) can be
explained by claims coded as COVID. The 0–44 age band exhibited the highest A/E ratio across the pandemic period
and has consistently shown the highest A/E by quarter since the middle of 2021. The 45–64 age band has thehighest excess mortality directly attributable to COVID (18.2%), whereas the 0–44 age band has the highest excess
mortality from non-COVID causes (18.8%), as shown in Table 5.7.
Table 5.7

EXCESS MORTALITY BY AGE BAND
Age
0-44
45-64
65+

Q3
2020

Q4
2020

Q1
2021

Q2
2021

Q3
2021

Q4
2021

Q1
2022

Q2
2022

Q3
2022

Q4
2022

131% 121% 121% 130% 180% 143% 125% 119% 125% 126%
124% 129% 130% 116% 162% 143% 125% 103% 107% 118%109% 129% 120% 100% 116% 116% 113%
96%
99%
100%
115% 128% 123% 107% 134% 126% 117%99%104% 107%
All Agesa
a. Includes only companies that provided Age splits; see second bullet at the beginning of Section 5.

Apr.
2020–
Dec.
2022
131%
125%
110%
116%

COVID
(%)

NonCOVID
(%)

Count
(%)

12.3%
18.2%
10.9%
13.0%

18.8%
6.8%
-0.7%
2.9%

8%
28%
64%
100%

Copyright © 2023 Society of Actuaries Research Institute23

The greater age band detail in Table 5.8 provides further insight on excess mortality by age. The working-age
population continues to see the highest A/E ratios. The 35–44 age band continues to have the highest cumulative
A/E during the pandemic and has the highest non-COVID excess mortality as well. It is worth noting that "nonCOVID" claims could include claims that are an indirect result of COVID but are not coded as such in the data.
Table 5.8

EXCESS MORTALITY BY DETAILED AGE BAND
Age

Q3
2020

Q4
2020

Q1
2021

Q2
2021

Q3
2021

Q4
2021

Q1
2022

Q2
2022

Q3
2022

Q4
2022

0-24
25-34
35-44
45-54
55-64
65-74
75-84
85+

124% 104% 101% 119% 128% 112%99%104% 119% 108%131% 120% 118% 132% 179% 137% 126% 121% 127% 123%133% 127% 129% 134% 201% 158% 134% 123% 126% 134%
126% 129% 132% 119% 179% 151% 128% 107% 112% 123%
122% 129% 129% 114% 152% 139% 123% 100% 105% 116%
115% 132% 130% 108% 130% 124% 116%95%
100% 104%113% 133% 123% 105% 119% 122% 121% 102% 107% 107%103% 124% 111%92%105% 107% 105%
91%
93%
92%
a
115%
128%
123%
107%
134%
126%
117%
99%
104%
107%
All Agesa. Includes only companies that provided Age splits; see second bullet at the beginning of Section 5.

Apr.
2020
–Dec.
2022
112%
131%
139%
130%
122%
116%
115%
103%
116%

COVID
(%)

NonCOVID
(%)

Count
(%)

2.8%
9.9%
17.2%
19.9%
17.4%
14.0%
11.3%
8.6%
13.0%

9.3%
21.1%
21.3%
10.0%
5.1%
1.5%
3.8%
-5.5%
2.9%

2%
2%
4%
9%
18%
17%
20%
27%
100%

Tables 5.9 and 5.10 have been added to separate out each quarter’s excess mortality by age band into the COVID
and non-COVID components. These views show that the Q3 2021 Delta wave onset had significant excess mortality
across all typical working age bands from 25 to 64, due to both COVID and non-COVID causes. Q4 2021 continued toshow very high COVID deaths in the 25 to 64 age bands, whereas the non-COVID excess mortality moderated.
Starting in Q2 2022, COVID deaths across all age groups have been relatively less, but non-COVID mortality
continues to be elevated in several age groups, including 25–44. Note that Q3 and Q4 2022 deaths may continue toshift from non-COVID to COVID as COD coding becomes more complete.
Table 5.9

EXCESS MORTALITY BY DETAILED AGE BAND—COVID ONLY

Age
0-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
Unknown
All Excl Unknown
All Agesa

Q1
2020
0%
1%
2%
2%
1%
1%
1%
1%
1%
1%
1%

Q2
2020
2%
7%
9%
13%
13%
13%
12%
13%
1%
12%
12%

Q3
2020
2%
7%
11%
13%
13%
10%
8%
6%
1%
9%
9%

Q4
2020
3%
8%
16%
22%
24%
26%
24%
21%
4%
22%
22%

Q1
2021
3%
10%
18%
28%
30%
29%
23%
17%
2%
23%
23%

Q2
2021
2%
6%
11%
13%
11%
7%
5%
2%
1%
7%
7%

Q3
2021
8%
35%
61%
58%
38%
21%
11%
6%
9%
23%
23%

Q4
2021
5%
21%
40%
42%
33%
21%
13%
8%
2%
21%
21%

Q1
2022
4%
12%
19%
26%
24%
21%
18%
12%
4%
19%
18%

Q2
2022
1%
1%
2%
2%
2%
2%
3%
3%
3%
2%
2%

Q3
2022
1%
1%
2%
2%
2%
3%
4%
4%
4%
3%
3%

Q4
2022
1%
0%
1%
1%
1%
1%
2%
3%
3%
2%
2%

Apr.
2020–
Dec.
2022
3%
10%
17%
20%
17%
14%
11%
9%
3%
13%
13%

a. Includes only companies that provided claims split by age; see second bullet at the beginning of Section 5.

Copyright © 2023 Society of Actuaries Research Institute24

Table 5.10

EXCESS MORTALITY BY DETAILED AGE BAND – NON-COVID ONLY

Age
0-24
25-34
35-44
45-54
55-64
65-74
75-84
85+
Unknown
All Excl Unknown
All Agesa

Q1
2020
93%
100%
105%
98%
97%
98%
100%
96%
56%
98%
98%

Q2
2020
113%
119%
113%
110%
104%
103%
102%
99%
55%
104%
103%

Q3
2020
123%
125%
122%
114%
110%
105%
105%
97%
61%
106%
106%

Q4
2020
101%
112%
112%
107%
105%
107%
108%
103%
51%
106%
106%

Q1
2021
98%
108%
112%
105%
99%
101%
99%
94%
59%
99%
99%

Q2
2021
117%
126%
123%
106%
103%
101%
101%
89%
45%
100%
100%

Q3
2021
120%
145%
140%
121%
115%
109%
108%
98%
62%
110%
110%

Q4
2021
107%
116%
118%
109%
105%
103%
109%
99%
76%
105%
105%

Q1
2022
95%
114%
116%
102%
99%
95%
103%
93%
53%
99%
99%

Q2
2022
103%
120%
121%
105%
99%
93%
99%
88%
68%
97%
97%

Q3
2022
118%
126%
124%
110%
103%
97%
103%
89%
87%
101%
101%

Q4
2022
107%
122%
133%
122%
114%
102%
105%
90%
99%
105%
105%

Apr.
2020–
Dec.
2022
109%
121%
121%
110%
105%
102%
104%
95%
65%
103%
103%

a. Includes only companies that provided claims split by age; see second bullet at the beginning of Section 5.
By sex, A/E ratios have generally been higher for males during the study period, as has the cumulative excess
mortality due to claims identified as COVID. However, that trend has not been as apparent in the two most recent
quarters. A recent uptick is also seen in the A/E ratio for exposures that do not have an indicator of Male or Female,although it remains a small percentage of the overall data. We have included the “Unknown” row in Table 5.11 todemonstrate this and to help see its impacts on the overall totals.
Table 5.11

EXCESS MORTALITY BY SEX
SexFemaleMale
Unknown
All Excl.
Unknown
Alla

Q3
2020

Q4
2020

Q1
2021

Q2
2021

Q3
2021

Q4
2021

Q1
2022

Q2
2022

Q3
2022

Q4
2022

114%
115%
148%

123%
130%
161%

119%
124%
149%

105%
107%
135%

130%
135%
179%

121%
128%
160%

113%
118%
162%

97%
99%
169%

102%
99%
319%

103%
99%
581%

Apr.
2020–
Dec.
2022
113%
115%
209%

115%

128%

122%

106%

133%

125%

117%

98%

100%

100%

115%

128%

123%

107%

134%

126%

117%

99%

104%

107%

COVID
(%)

NonCOVID
(%)

Count
(%)

11.3%
13.8%
16.4%

1.5%
1.6%
92.2%

32%
66%
1%

115%

13.0%

1.6%

99%

116%

13.0%

2.9%

100%

a. Includes only companies that provided claims split by age; see second bullet at the beginning of Section 5.

Copyright © 2023 Society of Actuaries Research Institute25

5.4 COMPANY SIZE
Contributing companies were assigned a size indicator of Large, Medium or Small per the criteria described inAppendix C.2.5. Results since April 2020 have indicated higher excess mortality (and higher percentage claims
identified as COVID) by decreasing company size. However, the results by Company Size are generally of the same
magnitude and are usually consistent in pattern from quarter to quarter. Ratios for Large Companies have tended to
be lower than those of other companies for most quarters. The spread by Company Size has narrowed during 2022,
and Q4 2022 was only the second quarter during the study period in which Medium companies exhibited the lowest
A/E ratio (102%).
Table 5.12

EXCESS MORTALITY BY COMPANY SIZE
Company
Size

Q3
2020

Q4
2020

Q1
2021

Q2
2021

Q3
2021

Q4
2021

Q1
2022

Q2
2022

Q3
2022

Q4
2022

Large
Medium
Small
All

113%
122%
123%
115%

127%
132%
136%
128%

122%
121%
132%
122%

106%
108%
110%
107%

132%
139%
146%
133%

124%
129%
134%
125%

116%
118%
123%
116%

98%
101%
103%
99%

102%
104%
103%
103%

106%
102%
107%
105%

Apr.
2020–
Dec.
2022
115%
118%
121%
115%

COVID
(%)

Count
(%)

12.9%
13.1%
15.0%
13.0%

79%
16%
4%
100%

Copyright © 2023 Society of Actuaries Research Institute26

Section 6: Detailed Cause of Death
Beginning with the June 2022 data submission, participating companies were asked to expand the study’s threeprevious cause of death (COD) groups (COVID-19, Accident, Illness) into 12 COD groupings. The December 2022 data
request expanded the number of categories to 15 by adding Respiratory, Cerebrovascular (including stroke) and
Alzheimer’s. A survey of the companies was completed prior to these requests to identify what groupings would befeasible to provide dating back to 2017. This survey, along with CDC cause of death groupings, informed thegroupings presented in this report. The mapping of these COD groups can be found in Appendix E.
Despite expansion of the COD categories, approximately 30% of claims still fall into the “All Other/Unknown” group,
and it would be ideal to decrease this number further. One challenge is that three of the 20 companies were notable to provide more detailed COD information back to 2017 than what was part of the original survey, and othercompanies did not track one or more ICD-10 diagnosis codes consistently over the course of the study period, sosome claims that otherwise would have been allocated to one of the new COD categories were labeled as“Unknown.”
The graphs in Figures 6.1 and 6.2 show excess mortality relative to baseline (2017–2019), ranked by the COD withthe most claim counts at the top (All Other/Unknown) and the fewest at the bottom (Alzheimer’s). The graphs havebeen split into two parts, with the top seven COD in the first and the bottom seven COD categories in the second.
Note that the COVID-19 COD is not a shown in these figures because there is no baseline mortality for COVID-19
from 2017 to 2019. Also, the 2022 incurred periods are incomplete with respect to COD; it is expected that the All
Other/Unknown category will decrease in excess mortality and other categories will increase in the 2022 periods as
COD reporting matures over time.
Figure 6.1

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—TOP SEVEN CAUSES OF DEATH
All Other /Unknown
Cardiovascular
CancerRespiratory
Accidents (Other)
SuicideAccidents (MV)
20%

40%
4Q22

60%
3Q22

2Q22

80%

100%

1Q22

2021

120%
2020

2019

140%

160%

2018

2017

180%

Copyright © 2023 Society of Actuaries Research Institute27

Figure 6.2

GROUP LIFE ACTUAL TO EXPECTED INCURRED MORTALITY—BOTTOM SEVEN CAUSES OF DEATH
Liver
Cerebrovascular
Drug Overdose
Homicide
Diabetes
Flu/Pneum.
Alzheimer’s
20%

40%
4Q22

3Q22

60%

80%

2Q22

1Q22

100%
2021

120%
2020

2019

140%

160%

2018

2017

180%

Note: As a result of the addition of the Respiratory category to the data request, many claims previously categorized
as Flu/Pneumonia were recategorized by study contributors as Respiratory.
The Committee notes that Cancer mortality rates continue to drop throughout the observation period of 2017–2022. Excess mortality for accidents, both Motor Vehicle and Other, was 10% –15% higher than baseline in 2021. The
2022 excess mortality for accidents appears to be developing above baseline as well, though the data are still too
incomplete to determine the degree to which it is higher. Diabetes and Liver deaths, often cited comorbidities with
COVID-19 deaths, appear to be elevated 5%–20% during the entire pandemic period; however, early indications
from the 2022 data suggest diabetes may be improving. Last, “deaths of despair,” particularly Drug Overdose and
Homicides, have increased around 55% and 20%, respectively.
Figure 6.3 displays the COD distribution in the 2017–2019 baseline period by count. Approximately half of the 2017–2019 baseline Group Life claims were Cardiovascular or Cancer. The top 10 COD groupings (excluding All
Other/Unknown) covered approximately two-thirds of all Group Life baseline claims. Although Figure 6.2 shows
substantial percentage increases in the Liver, Diabetes, Drug Overdose and Homicide causes of death during the
pandemic period, Figure 6.3 indicates that these causes constituted a relatively low percentage of overall deaths.

Copyright © 2023 Society of Actuaries Research Institute

28

Figure 6.3

GROUP LIFE CAUSE OF DEATH DISTRIBUTION, 2017–2019 BASELINE, BY COUNTAll Other / Unknown
Major Cardiovascular Diseases
Cancer
6.9%

31.0%

Respiratory
Accidents (Non-Motor Vehicle)
SuicideAccidents (Motor Vehicle)
Cerebrovascular, Including Stroke

22.9%

Liver
Diabetes
Influenza and Pneumonia
27.0%

Drug Overdose
Homicide
Alzheimer’s

Figure 6.4 displays the annual incidence trend of various CODs over the period of 2017–2021, with current
estimates for 2022 (not included in the trend). The trend for drug overdose has been steeply increasing over the five
years, with more modest but still noticeable upward patterns for Liver and Homicide. The trend for Suicide has been
flat, if not decreasing, over the five-year period. Accidents have also shown a significant uptick in 2021, particularly
for motor vehicle accidents. Although claims for 2022 are shown, it is expected that COD assignment for 2022 is not
yet fully complete, which contributes to the orange bar appearing lower than the incidence rates for prior periods
for some causes of death.

Copyright © 2023 Society of Actuaries Research Institute

29

Figure 6.4

ANNUAL INCIDENCE RATES FOR SELECT CAUSES OF DEATH FOR 2017–2022

Copyright © 2023 Society of Actuaries Research Institute30

Section 7: Exposure Trends
7.1 PREMIUMSThe Committee reviewed the premiums submitted for the study to determine if the premium exposure was stableor exhibited volatility during the experience period. Figure 7.1 indicates a gradual increase in premium exposure
during the experience period, as expected when wage inflation is considered. Supplemental premium is growing at afaster rate, and if current trends continue, supplemental premium will become the majority in the next few years.
The 2022 premiums in Figure 7.1 are reported premiums through December 2022. The overall trends in premium by
year shown below are consistent, which is helpful for validating the premium data used for calculating premium perlife (PPL) metrics and estimating covered lives when carriers could not provide this information.
Figure 7.1

REPORTED PREMIUM ($ BILLIONS) BY YEAR, 2017–2022
12.0
9.8
10.0

9.8

9.4

9.0

8.7

10.5

10.5

10.3

10.1

10.9
10.2

10.8

8.0

6.0

4.0

2.0

2017

2018

2019

2020

Basic

Supplemental

2021

2022

Copyright © 2023 Society of Actuaries Research Institute31

7.2 LIVESThe Committee also reviewed life-years of exposure (LYE) reported for the study. Figure 7.2 shows LYE from 2017
through 2022. A slight drop in LYE occurred in 2021, possibly because of disruptions from the COVID-19 pandemic.
Otherwise, basic LYE was relatively stable during the experience period, and supplemental LYE has been increasing
gradually.
Figure 7.2

LIFE-YEARS OF EXPOSURE (MILLIONS) BY YEAR, 2017–2022
98.0

97.6

96.2

95.4

100.0

98.8

96.5

90.0
80.0
70.0
60.0
50.0
40.0

35.3

34.0

33.6

33.0

32.1

31.5

30.0
20.0
10.0
2017

2018

2019

2020

Basic

Supplemental

2021

2022

Note: Previous iterations of this report displayed only LYE from companies that submitted life counts. This chart
includes “filled in” LYE using PPL estimates for companies that provided premiums but not lives.
Table 7.1 shows average premium per LYE based on the data provided for the study along with the change from theprior year. In 2020 the average premium per LYE increased by 0.9% for Basic coverages, which is lower than any
other period and likely related to the sharp increase in unemployment. All other Basic annual percentage changes
are between 1% and 2%. Supplemental has outpaced Basic in growth in all periods with the highest in 2020 and
2021 because consumers may have elected for additional coverage as the pandemic was at its peak.
Table 7.1

AVERAGE PREMIUM PER LIFE-YEARS OF EXPOSURE BY YEAR AND COVERAGE TYPE
Year

Average Premium per LYE

Change in Average Premium per LYE

2017

Basic
$102.8Supplemental$276.1

Basic
NA

Supplemental
NA

2018

$104.8$280.3

1.9%

1.5%

2019

$106.0$285.5

1.1%

1.9%

2020

$106.9$292.0

0.9%

2.3%

2021

$109.1$299.5

2.0%

2.5%

2022

$110.6$304.71.4%

1.8%

Note: Previous iterations of this report included only LYE from companies that submitted life counts. This table
includes “filled in” LYE using premium-per-life estimates for companies that provided premiums but not lives.

Copyright © 2023 Society of Actuaries Research Institute32

Table 7.2 shows average exposure per LYE and the change from the prior year. In 2021 the average exposure per
LYE decreased by 1.6% for Basic coverages but increased 1.2% for Supplemental coverages. Before 2021 thechanges in average premium per LYE were limited with most of the exposure growth coming from the Supplemental
line. The 3.9% increase in the Supplemental average exposure per LYE in 2022 may be attributed to employees
increasing their Supplemental benefit amounts because of the COVID-19 pandemic and above-average wage
growth.
Table 7.2

AVERAGE EXPOSURE PER LIFE-YEARS OF EXPOSURE BY YEAR AND COVERAGE TYPE
Year

Average Exposure per LYE
BasicSupplemental

Change in Average Exposure per LYE
BasicSupplemental

2017$7,950.6$2,624.2

NA

NA

2018

$8,013.8$2,673.8

0.8%

1.9%

2019

$8,135.9$2,752.0

1.5%

2.9%

2020

$8,169.7$2,799.1

0.4%

1.7%

2021

$8,039.0$2,831.6

-1.6%

1.2%

2022

$8,222.8$2,941.0

2.3%

3.9%

Copyright © 2023 Society of Actuaries Research Institute33

Section 8: Company Variations
8.1 VARIATIONS IN COVID-19 MORTALITY RESULTS
The survey showed that all participating companies had elevated Group Life mortality experience during the
pandemic. However, the level of excess mortality varied between carriers. To provide insight into the dispersion ofindustry experience, Tables 8.1 and 8.2 provide the quartile baseline and pandemic experience, ranked by highest
implied excess mortality percentage (by claim count) to lowest over the full pandemic period. The quartile incidence
rates and excess mortality ratios are the weighted average of the five contributing companies’ incidence rates ineach quartile.
Table 8.1

QUARTERLY SEASONALLY ADJUSTED INCURRED INCIDENCE RATES (BY COUNT)—COMPANY QUARTILES
Q2 2020–
Quartile
Baseline
2021 Q1 2022 Q2 2022 Q3 2022 Q4 2022
2022
Q4 2020
2.373
Quartile 1
3.052
3.206
2.962
2.506
2.587
2.626
2.670
2.621
Quartile 2
3.279
3.361
3.088
2.586
2.672
2.658
2.749
3.609
Quartile 3
4.256
4.307
4.271
3.621
3.826
3.961
3.919
4.094
Quartile 4
4.562
4.524
4.185
3.566
3.629
3.706
3.771
Total

3.242

3.873

3.949

3.777

3.198

3.331

3.405

3.427

Q2 2020–
Q4 2022
2.966
3.109
4.150
4.261
3.736

Table 8.2

QUARTERLY SEASONALLY ADJUSTED INCURRED A/E RATIOS (BY COUNT)—COMPANY QUARTILES
Q2 2020–
Quartile
Baseline
2021 Q1 2022 Q2 2022 Q3 2022 Q4 2022
2022
Q4 2020
2.373
Quartile 1
128.6% 135.1% 124.8% 105.6% 109.0% 110.7% 112.5%
2.621
Quartile 2
125.1% 128.3% 117.8%
98.7%
102.0% 101.4% 104.9%
3.609
Quartile 3
117.9% 119.3% 118.4% 100.3% 106.0% 109.7% 108.6%
4.094
Quartile 4
111.4% 110.5% 102.2%
87.1%
88.7%
90.5%
92.1%
Total

3.242

119.5%

121.8%

116.5%

98.6%

102.7%

105.0%

105.7%

Q2 2020–
Q4 2022125.0%
118.6%
115.0%
104.1%
115.2%

Copyright © 2023 Society of Actuaries Research Institute34

8.2 VARIATIONS IN COVID-19 CLAIM CODING PROCEDURES
Participating carriers were asked about the data sources and procedures they used to determine whether a claim
should be coded as a COVID-19 cause of death. Eighteen of the 20 carriers in the survey provided details on theirclaim coding procedures, and the Committee learned the following:•

Seventeen of the 18 respondents included the claim as a COVID-19 death if COVID-19 appeared anywhereon the death certificate.
• Eight of the 18 appeared to do everything in their power to research all available sources to create an
exhaustive tracking of all claims where COVID was a contributing cause. These companies used five or
more of the following sources to identify whether a death was caused by COVID-19:
o Primary cause of death on death certificate
o Secondary cause of death on death certificate
o Claim formo Communication with employer or beneficiaryo Obituaryo Communication with medical examiner or funeral home
• One carrier coded claims with cause of COVID-19 only when COVID-19 was identified as the primarycause of death on the death certificate.
• The other nine participating carriers generally classified a death as COVID-19 if it appeared anywhereon the death certificate.

8.3 VARIATIONS IN CLAIM REPORTING PATTERNSAppendix D.4 documents that incurred claim completion rates varied significantly from company to company. Upon
analyzing the differences, the 20 contributing companies were grouped into five “reporting speed” groups based on
similar reporting patterns.
The Committee investigated whether the company reporting speed groupings would be correlated to company size.
However, this was not the case. The Large, Medium and Small companies are well dispersed among the fivereporting speed categories.

Copyright © 2023 Society of Actuaries Research Institute35

Section 9: Comparisons to General U.S. Population Mortality Results
9.1 AGGREGATE EXCESS MORTALITY COMPARISONS
From April 2020 through December 2022, 149,290 incurred COVID claims were estimated to be in the Group Life
survey data, compared with approximately 1.1 million COVID deaths in the U.S. population during the same timespan according to the Centers for Disease Control and Prevention (CDC).3
Past studies that have compared insured mortality to population mortality have found that mortality among insured
lives tends to be lower. In particular, the SOA’s 2016 Group Term Life Mortality Study 4 found that, in the key
working ages, insured mortality is between 30% and 40% of general population mortality. This is often considered to
be a function of the fact that an employee generally is in good health to be actively at work, often has access tohealth care and tends to have a higher level of income (which is correlated with better health). Because themortality rates between the two populations tend to differ, the Committee analyzed the relative impact of the
COVID-19 pandemic on the Group Life data and the U.S. population by considering excess death percentages,
defined as the percentage increase in mortality rate over a baseline expectation.
The excess deaths in the Group Life data were determined via a comparison to average death rates in the Group Life
data from the 2017–2019 baseline, adjusted for seasonality. For the U.S. population, the Committee considered two
different expectation bases. The first basis was expected deaths published by the CDC,5 which were developed using
Farrington surveillance algorithms and historical data6 (CDC method). For the second method, the Committee
estimated expected deaths by computing the average CDC deaths from 2017 through 2019 and adjusting thisaverage for changes in U.S. population size, changes in the U.S. population demographic mix by age and sex, and thetrend for death rates by age group (Committee method).
Table 9.1 shows the evolution of this comparison by quarter using the Committee method for U.S. population
results. The results for Q2 2022 show substantially lower excess mortality in the Group Life population than the U.S.
population. The Q1 2022 Group Life excess mortality completed downward from the 20% shown in the previous
iteration of this report, and it is now approximately equal to the U.S. population excess mortality for the first quarterof 2022. Also, note that a CDC methodology change resulted in a restatement of the excess mortality for the U.S.
population for the first quarter of 2022.
Table 9.1

GROUP LIFE AND U.S. POPULATION EXCESS MORTALITY PERCENTAGES BY QUARTER

Group Life

Q2
2020
15%

Q3
2020
15%

Q4
2020
28%

Q1
2021
22%

Q2
2021
7%

Q3
2021
33%

Q4
2021
25%

Q1
2022
16%

Q2
2022
-1%

Q3
2022
3%

Q4
2022
5%

U.S. Population

20%

16%

26%

16%

5%

24%

18%

15%

2%

7%

7%

Difference

-5%

-1%

2%

6%

2%

9%

7%

1%

-3%

-4%

-2%

Age

3 National Center for Health Statistics, Provisional Death Counts for Coronavirus Disease 2019 (COVID-19),https://www.cdc.gov/nchs/nvss/vsrr/covid19/index.htm.
4 Society of Actuaries, 2016 Group Term Life Mortality Study & Tables, https://www.soa.org/resources/experience-studies/2016/2016-group-life-mortalitystudy/.
5 National Center for Health Statistics. Excess Deaths Associated with COVID-19, https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm.
6 More information can be found in the technical notes on the National Center for Health Statistics website, where the CDC publishes excess deaths:
https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm#techNotes.

Copyright © 2023 Society of Actuaries Research Institute36

9.2 EXCESS MORTALITY COMPARISON BY SEX AND AGE
Most participants in the Group Life Survey provided a distribution of claims by sex and age, but most were not able
to provide a distribution of exposure by sex and age. For this reason, the comparisons below show claim counts
unadjusted by any changes in exposure. The seasonality adjustment has also been removed to show a more directcomparison.
Table 9.2 shows the actual-to-baseline ratios by sex and broad age group. These excess percentages have beenadjusted for overall changes in exposure, but not for seasonal differences, either in total or by sex and age.
Table 9.2

EXCESS DEATH PERCENTAGES BY SEX AND BROAD AGE GROUP
Sex Age

Population

Q2–Q4
2020

Q1–Q2
2021

Q3–Q4
2021

Q1 2022

Q2 2022

Q3 2022

Q4 2022

Q1–Q4
2022

F 00-44

Group Life

19.0%

25.3%

55.3%

30.8%

9.3%

17.7%

31.2%

22.3%

F 00-44

U.S. Pop.

18.1%

21.4%

40.0%

24.7%

11.6%

15.4%

14.9%

16.7%

F 00-44

Difference

0.9%

4.1%

15.3%

6.1%

-2.3%

2.3%

16.3%

5.6%

M 00-44

Group Life

23.2%

27.4%

61.6%

31.8%

18.7%

19.3%

23.4%

23.3%

M 00-44

U.S. Pop.

27.4%

27.4%

44.8%

25.4%

20.8%

24.4%

18.2%

22.2%

M 00-44

Difference

-4.2%

0.0%

16.8%

6.4%

-2.1%

-5.1%

5.2%

1.1%

F 45-64

Group Life

16.1%

19.4%

38.5%

24.6%

-2.7%

1.6%

19.5%

10.8%

F 45-64

U.S. Pop.

15.0%

16.0%

32.0%

23.7%

-1.3%

0.4%

5.1%

7.0%

F 45-64

Difference

1.1%

3.4%

6.5%

0.9%

-1.4%

1.2%

14.4%

3.8%

M 45-64

Group Life

23.7%

27.6%

56.0%

34.8%

0.6%

1.9%

15.1%

13.1%

M 45-64

U.S. Pop.

20.7%

21.7%

35.2%

25.6%

1.1%

2.8%

5.9%

8.9%

M 45-64

Difference

3.0%

5.9%

20.8%

9.2%

-0.5%

-0.9%

9.2%

4.2%

F 65-99

Group Life

11.9%

9.7%

12.2%

14.9%

-7.9%

-5.9%

-6.9%

-1.4%

F 65-99

U.S. Pop.

16.8%

11.8%

15.6%

24.0%

0.7%

3.6%

14.4%

10.7%

F 65-99

Difference

-5.1%

-2.1%

-3.4%

-9.1%

-8.6%

-9.5%

-21.3%-12.1%

M 65-99

Group Life

14.1%

12.2%

15.1%

19.5%

-8.1%

-9.7%

-8.0%

-1.5%

M 65-99

U.S. Pop.

22.1%

19.5%

22.8%

33.6%

4.2%

7.6%

17.5%

15.7%

M 65-99

Difference

-8.0%

-7.3%

-7.7%

-14.1%-12.3%-17.3%-25.5%-17.2%At the younger ages, the proportional impact on the Group Life Market was worse than in the U.S. population, but
at the older ages the relationship is reversed. In particular, in 2022 the older ages with the Group Life market hadsignificantly better experience.
Please note also that the Q4 2022 Group Life results were as of December 31, 2022, and therefore include asignificant completion assumption. This assumption is determined in aggregate and may not be appropriate by sex
and age. For example, the Committee suspects that deaths for younger ages are reported more quickly than for
older ages, and, thus, the Q4 2022 results will likely not end up as unfavorable.
One of the observations from both the Group Life Survey and the U.S. population results is that the deaths havebeen higher than expected, even after excluding explicit COVID-19 deaths. This comparison is captured in Table 9.3.

Copyright © 2023 Society of Actuaries Research Institute37

Table 9.3

EXCESS DEATH PERCENTAGES, EXCLUDING COVID-19, BY SEX AND BROAD AGE GROUP
Sex Age

Population

Q2–Q4
2020

Q1–Q2
2021

Q3–Q4
2021

Q1 2022

Q2 2022

Q3 2022

Q4 2022

Q1–Q4
2022

F 00-44

Group Life

10.7%

15.1%

21.4%

17.0%

7.4%

15.7%

29.8%

17.5%

F 00-44

U.S. Pop.

12.7%

15.0%

20.5%

14.4%

10.6%

14.1%

14.0%

13.3%

F 00-44

Difference

-2.0%

0.1%

0.9%

2.6%

-3.2%

1.6%

15.8%

4.2%

M 00-44

Group Life

15.2%

17.3%

25.3%

18.0%

17.3%

18.1%

22.6%

19.0%

M 00-44

U.S. Pop.

22.3%

21.9%

28.4%

17.5%

20.1%

23.4%

17.7%

19.6%

M 00-44

Difference

-7.1%

-4.6%

-3.1%

0.5%

-2.8%

-5.3%

4.9%

-0.6%

F 45-64

Group Life

3.2%

2.4%

5.8%

5.1%

-4.1%

-0.8%

18.3%

4.6%

F 45-64

U.S. Pop.

3.1%

1.9%

6.4%

3.9%

-3.0%

-2.1%

3.2%

0.5%

F 45-64

Difference

0.1%

0.5%

-0.6%

1.2%

-1.1%

1.3%

15.1%

4.1%

M 45-64

Group Life

6.9%

5.7%

11.6%

8.2%

-1.0%

0.2%

14.1%

5.4%

M 45-64

U.S. Pop.

7.0%

6.5%

9.6%

6.7%

-0.2%

0.9%

4.5%

3.0%

M 45-64

Difference

-0.1%

-0.8%

2.0%

1.5%

-0.8%

-0.7%

9.6%

2.4%

F 65-99

Group Life

0.1%

-1.3%

2.0%

2.4%

-9.8%

-8.9%

-8.7%

-6.2%

F 65-99

U.S. Pop.

2.1%

-0.2%

4.4%

9.1%

-1.4%

-0.1%

11.0%

4.7%

F 65-99

Difference

-2.0%

-1.1%

-2.4%

-6.7%

-8.4%

-8.8%

-19.7%-10.9%

M 65-99

Group Life

-0.1%

-1.8%

2.0%

2.7%

-10.5%-13.3%-10.0%-7.8%

M 65-99

U.S. Pop.

4.2%

3.5%

8.3%

13.4%

1.7%

3.2%

13.5%

8.0%

M 65-99

Difference

-4.3%

-5.3%

-6.3%

-10.7%-12.2%-16.5%-23.5%-15.8%For the older ages, the Group Life experience excluding COVID-19 is actually below expectations, whereas the U.S.
population remains above expectations. For the younger ages, both populations show elevated mortality, although
this trend is worse for the under-age-45 population than for ages 45–64.
To visualize the differences by sex and age and over time, Figures 9.1 through 9.6 show ratios of actual deaths tobaseline expectations by month and by sex and age group. Because of the heavy reliance on completion factors in
the most recent month of data, December 2022 has been omitted from these charts.

Copyright © 2023 Society of Actuaries Research Institute

38

Figure 9.1

EXCESS DEATH PERCENTAGES, EXCLUDING COVID-19, FEMALES UNDER AGE 45
Group Life

140%

U.S. Population

130%
120%
110%
100%
90%

Jun-22

Sep-22Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Mar-21

Dec-20Jun-20

Sep-20Dec-19Mar-20Jun-19Sep-19Mar-19Dec-18Jun-18

Sep-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

Figure 9.2

EXCESS DEATH PERCENTAGES, EXCLUDING COVID-19, MALES UNDER AGE 45
Group Life

140%

U.S. Population

130%
120%
110%
100%
90%

Mar-22

Sep-21

Dec-21

Jun-21

Mar-21

Dec-20Jun-20

Sep-20Dec-19Mar-20

Sep-19Jun-19Mar-19Dec-18Jun-18

Sep-18Dec-17Mar-18

Sep-17

Jun-17Mar-17

Dec-16

80%

Males show a little more consistent elevated deaths in both populations than do females.

Copyright © 2023 Society of Actuaries Research Institute

39

Figure 9.3

EXCESS DEATH PERCENTAGES, EXCLUDING COVID-19, FEMALES AGES 45–64
Group Life

140%

U.S. Population

130%
120%
110%
100%
90%

Jun-22

Sep-22Jun-22

Sep-22Mar-22Mar-22

Sep-21

Dec-21
Dec-21

Jun-21

Mar-21

Dec-20Jun-20

Sep-20Dec-19Mar-20Jun-19Sep-19Mar-19Dec-18Jun-18

Sep-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

Figure 9.4

EXCESS DEATH PERCENTAGES, EXCLUDING COVID-19, MALES AGES 45–64
Group Life

140%

U.S. Population

130%
120%
110%
100%
90%

Sep-21

Jun-21

Mar-21

Dec-20Jun-20

Sep-20Dec-19Mar-20

Sep-19Jun-19Mar-19Dec-18Jun-18

Sep-18Dec-17Mar-18

Sep-17

Jun-17Mar-17

Dec-1680%

For this age group also, males show somewhat more elevated mortality in both populations.

Copyright © 2023 Society of Actuaries Research Institute40

Figure 9.5

EXCESS DEATH PERCENTAGES, EXCLUDING COVID-19, FEMALES AGES 65–99
Group Life

140%

U.S. Population

130%
120%
110%
100%
90%

Jun-22

Sep-22Jun-22

Sep-22Mar-22Mar-22

Sep-21

Dec-21
Dec-21

Jun-21

Mar-21

Dec-20Jun-20

Sep-20Dec-19Mar-20Jun-19Sep-19Mar-19Dec-18Jun-18

Sep-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

Figure 9.6

EXCESS DEATH PERCENTAGES, EXCLUDING COVID-19, MALES AGES 65–99
Group Life

140%

U.S. Population

130%
120%
110%
100%
90%

Sep-21

Jun-21

Mar-21

Dec-20Jun-20

Sep-20Dec-19Mar-20

Sep-19Jun-19Mar-19Dec-18Jun-18

Sep-18Dec-17Mar-18

Sep-17

Jun-17Mar-17

Dec-1680%

For older males, the Group Life experience has been consistently better than the U.S. population throughout the
pandemic, but for females this trend began to emerge more significantly in late 2021 into 2022.
Table 9.4 adjusts the U.S. population overall ratio of actual-to-baseline deaths to match what it would have been if
the distribution of baseline deaths were to match the Group Life distributions by sex and age.

Copyright © 2023 Society of Actuaries Research Institute41

Table 9.4

GROUP LIFE AND U.S. POPULATION EXCESS MORTALITY PERCENTAGES BY QUARTER WITH ADJUSTMENT FOR SEXAGE DEMOGRAPHICS (NO SEASONAL ADJUSTMENT)
Population

Q2–Q4
2020

Q1–Q2
2021

Q3–Q4
2021

Q1 2022

Q2 2022

Q3 2022

Q4 2022

Q1–Q4
2022

Group Life

117.3%

116.2%

127.5%

122.7%

95.9%

96.5%

101.7%

104.2%

U.S. Population

122.5%

118.8%

125.5%

130.3%

105.2%

108.2%

116.4%

115.0%

Difference

-5.2%

-2.6%

2.0%

-7.6%

-9.3%

-11.7%-14.7%-10.8%

Adjusted U.S. Pop.

123.1%

120.3%

128.0%

131.3%

105.7%

108.6%

116.0%

115.4%

Adjusted Difference

-5.8%

-4.1%

-0.5%

-8.6%

-9.8%

-12.1%-14.3%-11.2%

When adjusting for sex and age, very little change is seen in the comparison of Group Life results to U.S. population
results. This suggests that differences in the sex-age demographics do not explain much of the difference in theexcess mortality.
9.3 EXCESS MORTALITY COMPARISON BY CAUSE OF DEATH
Carriers were asked to provide 15 different causes of death, including COVID-19. The CDC provides detailed cause ofdeath (ICD-10 Code), which can be mapped to the 15 Group Life CODs using the definitions listed in Appendix E.
Using information furnished by the Group Life survey participants and the CDC, the Committee investigateddifferences in excess mortality by cause of death. Both the CDC and Group Life datasets tend to have a high level of
unknown causes for more recent deaths because it often takes time to investigate the actual causes. The CDC
suppresses deaths due to external causes for six months to allow time to do a full assessment. For this reason, thissection includes only the first six months of deaths in 2022.
Seasonality can be very important for causes of death, so rather than rely on the overall seasonal adjustments
describe earlier in this report, the Committee compared deaths in the years 2020–2022 to the same months in thebaseline period. For example, 1Q 2021 is be compared to the average from the first quarters of the years 2017
through 2019.
Table 9.5 compares the causes of deaths between the two populations. These excess percentages have beenadjusted for overall changes in exposure, but not for seasonal differences, either in total or by diagnosis.

Copyright © 2023 Society of Actuaries Research Institute42

Table 9.5

GROUP LIFE AND U.S. POPULATION EXCESS MORTALITY PERCENTAGES BY QUARTER, ALL AGES
Percent Change in Claim Counts

Baseline Percent ofClaims2020

2021

2022: First 6 Months
Group
U.S.
Life
Population
10.9%
14.2%

Group
Life
31.1%

U.S.
Population
23.2%

Group
Life
8.6%

U.S.
Population
10.9%

Group
Life
11.2%

U.S.
Population
12.5%

27.0%

23.1%

2.3%

6.5%

1.7%

6.3%

Cancer

22.9%

21.1%

-4.1%

0.5%

-5.9%

1.0%

Respiratory

6.9%

7.8%

-1.4%

-2.5%

-4.3%

-6.2%

3.0%

3.2%

9.7%

8.9%

14.6%

17.1%

8.5%

10.2%

2.2%

1.7%

-5.5%

-3.6%

0.2%

1.1%

-5.3%

4.4%

Accidents (Motor Vehicle)

1.9%

1.4%

0.3%

6.6%

10.6%

18.6%

13.6%

Cerebrovascular, Stroke

1.3%

5.2%

1.7%

8.2%

-5.5%

9.9%

Liver

1.1%

1.5%

4.2%

20.1%

14.9%

31.6%

2.3%
12.5%
2.1%

Drug Overdose

0.6%

1.8%

45.0%

42.0%

56.1%

67.7%

42.0%

68.5%

Diabetes

0.6%

3.0%

23.7%

19.6%

5.4%

20.9%

17.5%

Influenza and Pneumonia

0.6%

1.9%

15.2%

-2.4%

-3.9%

-23.6%-34.7%

Homicide

0.6%

0.7%

18.8%

28.6%

18.7%

36.1%

3.6%
30.5%
15.3%

Alzheimer’s

0.2%

4.3%

32.4%

10.4%

1.7%

-1.8%

-2.0%

-2.9%

11.0%

12.4%

18.3%

14.7%

9.6%

9.6%

Cause of DeathAll Other / Unknown
Major Cardiovascular
DiseasesAccidents (Non–Motor
Vehicle)Suicide

COVID-19

-6.1%
14.1%
12.8%

5.0%
0.4%
-10.5%

10.9%
27.1%

30.9%

There is no baseline expectation for COVID-19, so these are compared to the total deaths across all causes. The
causes are sorted by total baseline claims for Group Life. The All Other/Unknown category is higher for Group Lifebecause some carriers were not able to provide all causes of death consistently back to 2017, as described in
Section 6. All U.S. population deaths have an established cause except for those listed as ill-defined (ICD-10 R99).
The higher proportion in the category in the first half of 2022 are likely due to deaths for which the cause is not yet
established.
The distributions of causes of excess deaths are fairly similar between the two populations. Group Life excess deaths
are generally lower for drug overdoses, liver disease, cerebrovascular, homicides and cancer, and relatively higher
for Alzheimer’s, non–motor vehicle accidents, and flu and pneumonia.
The percentage change can be misleading because a high percentage increase can be caused by relatively few
excess deaths when the overall death level in the category is small. Table 9.6 gives a similar view, except that theexcess deaths for each cause are divided by the total baseline death expectations. For example, in the Group Lifedata, the excess deaths due to major cardiovascular disease in 2021 was 0.5% of the baseline expectation.

Copyright © 2023 Society of Actuaries Research Institute43

Table 9.6

GROUP LIFE AND U.S. POPULATION EXCESS MORTALITY PERCENTAGES BY QUARTER
Number of Extra Deaths Divided by Total Baseline

Baseline Percent ofClaims
Cause of DeathAll Other / Unknown
Major Cardiovascular
Diseases
Cancer2020

2021

2022: First 6 Months
Group
U.S.
Life
Population
3.4%
3.3%

Group
Life
31.1%

U.S.
Population
23.2%

Group
Life
2.7%

U.S.
Population
2.5%

Group
Life
3.5%

U.S.
Population
2.9%

27.0%

23.1%

0.6%

1.5%

0.5%

1.5%

-1.7%

1.2%

22.9%

21.1%

-0.9%

0.1%

-1.3%

0.2%

-3.2%

0.1%

Respiratory
Accidents (Non-Motor
Vehicle)Suicide

6.9%

7.8%

-0.1%

-0.2%

-0.3%

-0.5%

-0.9%

-0.9%

3.0%

3.2%

0.3%

0.3%

0.4%

0.6%

0.2%

0.3%

2.2%

1.7%

-0.1%

-0.1%

0.0%

0.0%

-0.1%

0.1%

Accidents (Motor Vehicle)

1.9%

1.4%

0.0%

0.1%

0.2%

0.3%

0.0%

0.2%

Cerebrovascular, Stroke

1.3%

5.2%

0.0%

0.4%

-0.1%

0.5%

-0.2%

0.6%

Liver

1.1%

1.5%

0.0%

0.3%

0.2%

0.5%

0.0%

0.4%

Drug Overdose

0.6%

1.8%

0.3%

0.7%

0.3%

1.2%

0.3%

1.2%

Diabetes

0.6%

3.0%

0.1%

0.6%

0.0%

0.6%

0.0%

0.5%

Influenza & Pneumonia

0.6%

1.9%

0.1%

0.0%

0.0%

-0.5%

-0.2%

-0.8%

Homicide

0.6%

0.7%

0.1%

0.2%

0.1%

0.2%

0.1%

0.2%

Alzheimer’s

0.2%

4.3%

0.1%

0.4%

0.0%

-0.1%

0.0%

-0.1%

11.0%

12.4%

18.3%

14.7%

9.6%

9.6%

COVID-19

Aside from COVID-19, we see that All Other/Unknown is the largest contributor to excess deaths in all three years
and for both populations. The Committee does not have any details on these claims from the Group Life survey, butthese details are available for the U.S. population (see Table 9.7 below).
The next highest category is major cardiovascular disease, but this has decreased within the Group Life results
within 2022. The increase in drug overdoses is more significant within the U.S. population than Group Life, whereas
liver disease (cirrhosis) is elevated in both populations. Diabetes deaths are elevated in both populations but
represent a much smaller proportion of deaths for Group Life.
To help visualize the dynamics, Figures 9.7 through 9.12 show deaths relative to the baseline by cause and by monthfor the two populations. The deaths are compared to the same month in the baseline period.

Copyright © 2023 Society of Actuaries Research Institute

44

Figure 9.7

DEATHS RELATIVE TO BASELINE—MAJOR CARDIOVASCULAR DISEASE
Group Life

120%

U.S. Population

110%

100%

90%

Jun-22Mar-22

Dec-21

Jun-21

Sep-21

Mar-21

Sep-20Dec-20Jun-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

The drop-off in cardiovascular deaths in the Group Life data is evident. The low level in the last few months is likely
due to claims with causes that are not yet established, but the decrease in early 2022 is likely to persist after all thecauses have been established.
Figure 9.8

DEATHS RELATIVE TO BASELINE—DRUG OVERDOSES

Jun-22Mar-22

Dec-21

Jun-21

Sep-21

Mar-21

Sep-20Dec-20Jun-20Mar-20Dec-19Jun-19U.S. Population

Sep-19Mar-19Sep-18Jun-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-16

Dec-18Group Life

200%
190%
180%
170%
160%
150%
140%
130%
120%
110%
100%
90%
80%

Copyright © 2023 Society of Actuaries Research Institute

45

Figure 9.9

DEATHS RELATIVE TO BASELINE—ALL OTHER/UNKNOWNGroup Life

130%

U.S. Population

120%
110%
100%
90%

Jun-22

Sep-22Mar-22

Sep-21

Dec-21

Jun-21

Mar-21

Dec-20Jun-20

Sep-20Dec-19Mar-20Jun-19Sep-19Mar-19Dec-18Jun-18

Sep-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

Because the unknown numbers are so high in recent months we have excluded the last three months for the U.S.
population and the last six months for Group Life.
Figure 9.10

DEATHS RELATIVE TO BASELINE—LIVER DISEASE
Group Life

150%

U.S. Population

140%
130%
120%
110%
100%
90%

Jun-22Mar-22

Dec-21

Sep-21

Jun-21

Mar-21

Dec-20

Sep-20Jun-20Mar-20Dec-19Sep-19Jun-19Mar-19Sep-18Dec-18Jun-18Mar-18Dec-17

Sep-17

Jun-17Mar-17

Dec-1680%

Figure 9.10 shows that the proportional impact of liver disease was more significant for the U.S. population than forGroup Life.

Copyright © 2023 Society of Actuaries Research Institute46

Figure 9.11

DEATHS RELATIVE TO BASELINE—DIABETESGroup Life

160%

U.S. Population

150%
140%
130%
120%
110%
100%
90%
Jun-22Mar-22

Dec-21

Jun-21

Sep-21

Mar-21

Sep-20Dec-20Jun-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

Diabetes deaths remain elevated for the U.S. population but have recently declined for Group Life.
Figure 9.12

DEATHS RELATIVE TO BASELINE—CANCER
Group Life

110%

U.S. Population

100%

90%

Jun-22Mar-22

Dec-21

Jun-21

Sep-21

Mar-21

Sep-20Dec-20Jun-20Mar-20Dec-19Jun-19Sep-19Mar-19Sep-18Dec-18Jun-18Dec-17Mar-18Jun-17

Sep-17Mar-17

Dec-1680%

Here we see cancer declining fairly significantly for Group Life, but not for the U.S. population.
Since the All Other/Unknown category is significantly elevated, the Committee researched the most prominent ICD10 codes that make up this group in the U.S. population. Table 9.7 shows the top 20 codes for excess deaths, sorted
by excess deaths in 2020 and 2021. 2022 was not included because the cause for some deaths may not yet be
determined.

Copyright © 2023 Society of Actuaries Research Institute47

Table 9.7

U.S. POPULATION EXCESS MORTALITY BY ICD-10 CODE FOR “ALL OTHER/UNKNOWN”
Excess Deaths
2020
2021

ICD-10 Description
Senile degeneration of brain, not elsewhere classified
Parkinson’s disease
Essential (primary) hypertension
Unspecified severe protein-energy malnutrition
Hyperlipidemia, unspecified
Vascular dementia, unspecified
Mental and behavioral disorders due to use of alcohol, harmful use
Mental and behavioral disorders due to use of alcohol, dependence syndrome
Hypertensive renal disease with renal failure
Unspecified protein-energy malnutrition
Chronic kidney disease, stage 5
Metabolic disorder, unspecified
Urinary tract infection, site not specified
Other obesity
Coronavirus infection, unspecified
Obesity, unspecified
Other specified degenerative diseases of nervous system
Acute renal failure, unspecified
Gastrointestinal hemorrhage, unspecified

13,589
6,538
3,931
2,821
3,136
3,355
2,117
2,063
1,822
1,692
1,616
1,090
902
1,246
1,887
972
1,375
395
1,009

18,480
4,807
4,237
4,631
4,007
2,641
2,827
2,631
2,290
2,294
2,107
2,046
1,975
1,547
708
1,586
1,136
2,097
1,405

Fatty (change of) liver, not elsewhere classified

796

1,229

Many of these conditions appear to be due to general poor health that may have been exacerbated by COVID-19.

9.3 EXCESS MORTALITY COMPARISON BY GEOGRAPHIC REGIONThe CDC method described above for U.S. population expected deaths enables a comparison of excess death
percentages by month and geographic region. Tables 9.8 and 9.9 display the excess death percentages by quarterand region for the U.S. population and the Group Life survey data, respectively. The “Total Excl. Other” row shows
the weighted average A/E ratio for claims that could be allocated to the four regions.
Table 9.8

U.S. POPULATION EXCESS DEATH PERCENTAGE BY QUARTER AND GEOGRAPHIC REGION
RegionMidwest
Northeast
Southeast
West
Total Excl. Other
Total

Q2–
Q4
2020
20.9%
25.0%
20.6%
18.7%
21.2%
21.1%

Q1–
Q2
2021
7.0%
10.9%
17.2%
17.9%

Q3–
Q4
2021
18.3%
11.6%
27.9%
23.6%

Q1
2022

Q2
2022

Q3
2022

Q4
2022

Q2 2020–
Q4 2022% of Total
COVID Deaths

19.3%
17.6%
22.7%
21.0%

-0.4%
-0.1%
2.5%
3.6%

4.3%
3.6%
9.7%
11.2%

8.7%
8.5%
8.8%
13.1%

13.2%
13.6%
17.7%
17.1%

13.8%
13.7%

21.6%
21.5%

21.0%
20.5%

3.6%
1.6%

11.2%
7.7%

13.1%
9.6%

15.7%
15.7%

21.1%
21.4%
38.2%
19.3%
99.6%
100.0%

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48

Table 9.9

GROUP LIFE COVID-19 SURVEY EXCESS DEATH PERCENTAGE BY QUARTER AND GEOGRAPHIC REGION
RegionMidwest
Northeast
Southeast
West
Total Excl. Other
Total

Q2-Q4
2020
18.0%
23.5%
21.2%
19.5%

Q1-Q2
2021
6.6%
15.1%
21.7%
17.6%

Q3-Q4
2021
24.4%
19.9%
42.5%
29.2%

20.5%
19.5%

15.4%
14.5%

30.6%
29.2%

Q1
2022
17.1%
18.4%
18.7%
13.4%
17.4%
16.5%

Q2
2022
-2.7%
1.6%
-1.2%
0.2%
-0.8%
-1.4%

Q3
2022
2.0%
2.0%
6.1%
0.5%
3.2%
2.7%

Q4
2022
13.6%
5.3%
4.9%
-10.4%
5.0%
5.0%

Q2 2020–
Q4 2022
13.3%
15.3%
20.0%
14.1%
16.2%
15.3%

% of Total
COVID Deaths
25.9%
17.5%
41.1%
15.0%
0.4%
100.0%

Figure 9.13 shows excess death percentages by region for both the Group Life data and the U.S. population data.
Figure 9.13

EXCESS DEATH PERCENTAGES BY GEOGRAPHIC REGION, APRIL 2020 THROUGH DECEMBER 2022

For the April 2020 through December 2022 period, the Southeast shows the highest excess mortality for both theGroup Life data and the U.S. population. The Midwest experienced the lowest excess mortality for both datasets
during the pandemic period, though significant variations by season have been seen. For the Group Life data, theSoutheast is the only region with higher-than-average excess mortality. The largest contrast between the Group Life
data and the U.S. population data is in the West, where the U.S. population has excess mortality 3.0% (additive)
higher than the U.S. population.

Copyright © 2023 Society of Actuaries Research Institute49

9.4 EXCESS MORTALITY COMPARISON BY VACCINATION UPTAKEThe Committee researched vaccination uptake statistics by state using data furnished by the CDC. 7 Using thisinformation, the Committee analyzed excess mortality percentages by statewide vaccination rates8 in the Group Life
population and the U.S. population (using the CDC method for expected deaths). 9
The scatterplots in Figures 9.14 through 9.19 show the correlation between the statewide percent of the population
with a completed primary vaccine series as of June 30, 2021, and excess mortality in the U.S. population and theGroup Life data. Figures 9.14 and 9.15 present true-ups of the third quarter of 2021 plots shown in previous
versions of this report. Figures 9.16 and 9.17 present the analysis for the subsequent period of October 2021
through December 2022. Figures 9.18 and 9.19 show the correlation for the entire period of July 2021 throughDecember 2022. The scatterplots in Figures 9.20 and 9.21 show the correlation between the statewide percent of
the population with a completed primary vaccine series and an additional dose (booster) as of December 31, 2021,
and excess mortality in the U.S. population and the Group Life data for the period of January 2022 throughDecember 2022.
Figure 9.14

U.S. POPULATION EXCESS MORTALITY BY STATEWIDE VACCINATION RATE, JULY THROUGH SEPTEMBER 2021
100%

Excess Mortality Estimate

80%

y = -0.979x + 0.656
R² = 0.410

60%
40%
20%
0%
-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated at 6/30/2021
Midwest

Northeast

Southeast

West

7Centers for Disease Control and Prevention, COVID-19 Vaccinations in the United States, Jurisdiction: https://data.cdc.gov/Vaccinations/COVID-19-

Vaccinations-in-the-United-States-Jurisdi/unsk-b7fc. In these CDC data, the percent fully vaccinated means the percent of people who have had the second
dose of a two-dose vaccine or one dose of a single-dose vaccine.
8Although COVID-19 vaccines were approved only for ages 12 and older as of June 30, 2021, the denominators for the vaccination rates shown in thissubsection are total state populations including all ages.
9National Center for Health Statistics, Excess Deaths Associated with COVID-19: https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm. Notethat the CDC excess deaths are reported on a weekly basis. In this section of the report, for the population graphs, actual and excess deaths for a particular
reporting period are for weeks that ended in that reporting period.

Copyright © 2023 Society of Actuaries Research Institute

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Figure 9.15

GROUP LIFE EXCESS MORTALITY BY STATEWIDE VACCINATION RATE, JULY THROUGH SEPTEMBER 2021
100%

Excess Mortality Estimate

80%

y = -1.539x + 1.033
R² = 0.349

60%
40%
20%
0%
-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated at 6/30/2021
Midwest

Northeast

Southeast

West

Figure 9.16

U.S. POPULATION EXCESS MORTALITY BY STATEWIDE VACCINATION RATE, OCTOBER 2021 THROUGH DECEMBER
2022
100%

Excess Mortality Estimate

80%

y = -0.116x + 0.177
R² = 0.057

60%

40%

20%

0%

-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated at 6/30/2021
Midwest

Northeast

SoutheastWest

Copyright © 2023 Society of Actuaries Research Institute

51

Figure 9.17

GROUP LIFE EXCESS MORTALITY BY STATEWIDE VACCINATION RATE, OCTOBER 2021 THROUGH DECEMBER 2022
100%

Excess Mortality Estimate

80%

y = -0.160x + 0.173
R² = 0.015

60%
40%
20%
0%
-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated at 6/30/2021
Midwest

Northeast

Southeast

West

Figure 9.18

U.S. POPULATION EXCESS MORTALITY BY STATEWIDE VACCINATION RATE, JULY 2021 THROUGH DECEMBER 2022
100%

Excess Mortality Estimate

80%
y = -0.251x + 0.252
R² = 0.188
60%

40%

20%

0%

-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated at 6/30/2021
Midwest

Northeast

SoutheastWest

Copyright © 2023 Society of Actuaries Research Institute

52

Figure 9.19

GROUP LIFE EXCESS MORTALITY BY STATEWIDE VACCINATION RATE, JULY 2021 THROUGH DECEMBER 2022
100%

Excess Mortality Estimate

80%

y = -0.390x + 0.317
R² = 0.086

60%
40%
20%
0%
-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated at 6/30/2021
Midwest

Northeast

Southeast

West

Figure 9.20

U.S. POPULATION EXCESS MORTALITY BY STATEWIDE VACCINATION RATE WITH PRIMARY SERIES AND ADDITIONAL
DOSE, JANUARY 2022 THROUGH DECEMBER 2022
100%

Excess Mortality Estimate

80%
y = -0.004x + 0.098
R² = 0.000
60%

40%

20%

0%

-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated + Additional Dose at 12/31/2021
Midwest

Northeast

SoutheastWest

Copyright © 2023 Society of Actuaries Research Institute

53

Figure 9.21

GROUP LIFE EXCESS MORTALITY BY STATEWIDE VACCINATION RATE WITH PRIMARY SERIES AND ADDITIONAL
DOSE, JANUARY 2022 THROUGH DECEMBER 2022
100%

Excess Mortality Estimate80%
y = 0.257x - 0.036
R² = 0.029

60%
40%
20%
0%
-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated + Additional Dose at 12/31/2021
Midwest

Northeast

SoutheastWest

Comparing state-level excess mortality percentage estimates to estimated COVID-19 vaccinated percentages showsa moderate negative correlation for both the U.S. population and the Group Life data for the third quarter of 2021.
For subsequent periods, although some negative correlation was still seen in most periods, it was less pronounced
than the third quarter of 2021. Note that Figure 9.21, which looks at the correlation based on the percent of the
population with a completed primary vaccine series and an additional dose (booster) as of December 31, 2021,
shows a small positive correlation for the Group Life data for the 2022 period, but with a very low R2 statistic, whichindicates that vaccination rate does not explain much of the variation in excess mortality. Other variables in addition
to COVID-19 vaccination rates are certainly relevant for explaining the excess mortality trends observed in the
United States, and various potential reasons likely can be identified for the lower degree of negative correlation in
the later period relative to the earlier period. Contributing factors for this shift might include varying degrees ofvaccine effectiveness against different variants of the virus or a higher degree of natural immunity because of past
infections in the later periods.
The color-coded geographic regions in Figures 9.14 through 9.21 show some clustering of excess mortality results
regardless of vaccination percentage, especially in the U.S. population data. Climate and seasonality are possible
contributing factors to this observation because weather patterns in broad geographic regions may contribute tosimilar behavior patterns and levels of viral transmission for states within the same region, which may lead todifferent waves of the pandemic affecting different geographic regions at different times. State-level differences
may also be seen in preventative measures (e.g., social distancing and masking) that produce different transmission
and death rates. Finally, COVID-19 deaths do not explain all of the excess mortality observed in the datasets
presented here, and mortality patterns for other CODs may also influence the patterns shown above.

Copyright © 2023 Society of Actuaries Research Institute54

The data collected for the Group Life survey do not include county-level information to allow for a similar analysis at
the county level for the Group Life population. However, enough county-level information is available from the CDC
for at least a portion of the counties in the U.S. to allow for a similar analysis at the county level for the U.S.
population. Roughly 3,143 counties and county equivalents are found in the U.S. After filtering out counties withmissing data or gaps in data, roughly 1,950 remaining counties had sufficient data to complete this analysis.
Expected mortality was determined by applying the 2017–2019 county-specific population mortality rate from the
CDC10 to the estimated July 1, 2021, and July 1, 2022, populations for each county from the U.S. Census Bureau.11
Actual mortality was based on the CDC provisional mortality by county and by month. 12 Actual mortality was
adjusted for seasonality and the number of days in each calendar month. 13 The counties were then sorted andseparated into 50 bins by vaccination rate with an excess mortality percentage determined for each bin. The analysis
was completed only through the end of September 2022 to account for the lag in CDC reporting of deaths at thecounty level.
The scatterplots in Figures 9.22 and 9.23 show the correlation between the countywide percent of the population
with a completed primary vaccine series as of June 30, 2021, and the excess mortality in the U.S. population. Figure
9.22 shows the third quarter of 2021 for comparison to the state-level analysis in Figure 9.14. Figure 9.23 shows thesubsequent period of October 2021 through September 2022. The scatterplot in Figure 9.24 shows the correlation
between the countywide percent of the population with a completed primary vaccine series and an additional dose(booster) as of December 31, 2021, and excess mortality in the U.S. population for the period of January 2022
through September 2022.

10CDC WONDER, https://wonder.cdc.gov.

11County Population Totals and Components of Change: 2020–2022, https://www.census.gov/data/tables/time-series/demo/popest/2020s-counties-

total.html.
12About Provisional Mortality Statistics, 2018 through Last Month, https://wonder.cdc.gov/mcd-icd10-provisional.html.

13The seasonality factors were developed using the same logic as outlined in the SOA paper “2020 Excess Deaths in the U.S. General Population by Age andSex,” https://www.soa.org/resources/research-reports/2021/excess-deaths-gen-population/. As a simplifying assumption, the same set of countywide
seasonality factors were applied to all counties rather than developing a separate set of seasonality factors for each county based on the demographic mix
within each county.

Copyright © 2023 Society of Actuaries Research Institute55

Figure 9.22

U.S. COUNTY-SPECIFIC POPULATION EXCESS MORTALITY BY VACCINATION RATE, JULY THROUGH SEPTEMBER 2021
100%

Excess Mortality Estimate

80%

y = -0.6394x + 0.5395
R² = 0.6259

60%

40%

20%

0%

-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated at 06/30/2021

Figure 9.23

U.S. COUNTY-SPECIFIC POPULATION EXCESS MORTALITY BY VACCINATION RATE, OCTOBER 2021 THROUGHSEPTEMBER 2022
100%

Excess Mortality Estimate

80%

y = -0.2066x + 0.2474
R² = 0.6714

60%

40%

20%

0%

-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated at 06/30/2021

Copyright © 2023 Society of Actuaries Research Institute

56

Figure 9.24

U.S. COUNTY-SPECIFIC POPULATION EXCESS MORTALITY BY VACCINATION RATE WITH PRIMARY SERIES AND
ADDITIONAL DOSE, JANUARY 2022 THROUGH SEPTEMBER 2022
100%

Excess Mortality Estimate

80%

y = -0.1352x + 0.1874
R² = 0.2684

60%

40%

20%

0%

-20%
0%

10%

20%

30%

40%

50%

60%

70%

80%

% of Population Fully Vaccinated + Additional Dose at 12/31/2021

Similar to the state-level analysis for the U.S. population, the county-level analysis shows negative correlation
between the excess mortality percentage estimates and the percentages of the population that are fully vaccinated.
As was the case with the state-level analysis, the third quarter of 2021 shows a steeper slope than the subsequent
periods. In comparing the county-level and state-level graphs, the R2 statistics suggest a stronger fit at the county
level relative to the state level. However, the steeper slopes on the state-level graphs relative to the county-levelgraphs suggest a larger change in excess mortality per percentage change in vaccination rate at the state level.
Given the range of potential contributing factors for the shifting level of correlation between the vaccination rateand excess mortality, and for the clustering of results by geographic region, the Committee urges caution in drawing
definitive conclusions regarding the degree of causation between the vaccination rate and excess mortality or thegeographic clustering. Note that given the significant decline in correlation between mortality and state-level andcounty-level vaccination rates as time has passed from the initial uptake of the COVID-19 vaccines, the Committee
will likely omit this subsection from future reports unless a significant statistical relationship reemerges.

Copyright © 2023 Society of Actuaries Research Institute57

Section 10: Reliance and Limitations
In producing this report, the Committee relied upon data furnished by contributing companies and data publishedby the CDC. The Committee would like to stress that the data presented in this survey are emerging. Contributing
companies may true up these data over time. The Committee also notes that carriers submitted data in different
formats; it is possible that the homogenization of data submissions could introduce some unintended distortion in
the survey results. The reader should review the limitations noted throughout the report.

Copyright © 2023 Society of Actuaries Research Institute58

Section 11: List of Participating Companies
The Committee would like to thank the following companies that submitted data and made this COVID-19 mortality
survey possible:
Aflac
Dearborn National
Elevance
Guardian
The Hartford
Lincoln Financial Group
MetLife
Mutual of Omaha
New York Life Group Benefit Solutions
OneAmerica
Principal Financial
Reliance Standard
Renaissance
Securian Financial Group
Standard Insurance GroupSunLife Financial Group
SymetraUnum
USAbleVoya

Copyright © 2023 Society of Actuaries Research Institute

59

Appendix A: 2020 SOA Group Term Life COVID-19 Mortality Survey Data Request
PurposeThis is the data request for a Group Term Life Claim study intended to allow a quick assessment of the impact of the
COVID-19 pandemic on the Group Life industry—primarily by measuring the extra mortality occurring during the
pandemic as compared to prior periods. This high-level study will become a valuable data source for Group Life
insurers, since the industry wide COVID-19 claims will be significantly more credible than the claims experience forany one carrier.
TimingWe are requesting the initial data submission be provided by Friday, June 19th. We acknowledge that this is a tightturnaround, but due to the rapidly changing environment, time is of the essence. Please let us know ASAP if you
have a problem with this date or any element of this request. We plan to act quickly on the data—releasing an initialsummary report to participating carriers the week of July 6th.
The initial data request is for data from January 2017 through May 2020. We also plan to update the study monthly
throughout the duration of the pandemic. Please consider this when you build your queries for the initial request, sothat the monthly updates are easier to produce. We request that updates be submitted by the 3rd Friday of eachmonth. Contributors will receive a detailed summary report of their submitted data with some analysis of all thecontributed data after each monthly submission. The SOA will also be releasing summary reports of the aggregatedresults periodically throughout the duration of the study.
General Comments
Our goal is to measure patterns and trends rather than actual mortality rates. For the data request, this means weare more interested in how things change by month than whether they are 100% accurate or even consistent withother carrier submissions. We understand this data assembly will take some effort, and want to minimize
unnecessary data manipulation. To this end, please develop your submission as best you can to align with ourrequest, but more importantly, please ensure it is consistent over subsequent monthly updates.
Claim Data Request
Broadly, we are requesting summarized death claim information for your group life business with limited
segmentation. The limited segmentation will support further analysis/validation of observed trends. We hope all
carriers will be able to provide the Baseline data below. Please also provide the Segmentation if feasible, but we can
include your submission in the study even if these components are not readily available.
1. Baseline—The essential data requested is claim counts by incurred month, reported month, productsegment, and limited cause of death. Ideally, claim amounts can also be provided.
• Product Segment = Basic Life, Supp/Optional/Voluntary Life, and Retiree Life
• Cause of Death = COVID, Accident, and All Other
2.

Segmentation—We are also requesting claim counts and amounts for three separate segments—industry,
state, and age/sex. Data for each requested segment would be further split into the product and cause ofdeath categories referenced above.
• Industry = 2-digit SIC code is ideal• State = Based on residence, or work location if residence not available• Age/Sex = M/F/U, and 10-year age bands

Copyright © 2023 Society of Actuaries Research Institute

60

Claim Data Specifics
Again, as we will be looking at trends and patterns rather than actual mortality, it is most important that yoursubmission be consistent month to month. Nevertheless, the ideal submission should consider the following specificcriteria:• Include only group term life business. Exclude any GUL/GVUL, COLI/BOLI, 10/20-year group term, etc.
• Include both self-administered and list-billed business• Include employee, spouse, and child claims• Include or exclude portability and conversion claims—whichever is easier—based on your company
reporting.
• Include deaths from persons on waiver of premium; exclude active waivers• Include only death claims; exclude counts or amounts for various riders, especially living benefit riders or
critical illness riders• Include only the life insurance amount for accidental deaths• Exclude any interest payments or expenses
Exposure Data Request
As stated, this is not a mortality rate study, and we do not intend to calculate mortality rates. The purpose of
exposure data is to help explain and validate any observed trends. As with claims, we are requesting both high-level
exposure data, as well as exposure data by segment. However, the most critical information is exposures by month.
1.

Baseline—The essential data requested is earned premium by report month and product segment.
Optional data would include exposed lives by month.
• Product Segment = Basic Life, Supp/Optional/Voluntary Life, and Retiree Life

2.

Segmentation—We are also requesting exposure data for the segments—industry, state, and age/sex. Datafor each requested segment would be further split by product.
• Industry = 2-digit SIC code is ideal• State = Based on residence, or work location if residence not available• Age/Sex = M/F/U, and 10-year age bands

Exposure Data Specifics
We recognize that it can be difficult to provide exposed lives data, which is why we have selected earned premium
as the primary exposure metric. Exposed lives is certainly a valuable addition, if it is available. As with claims, westress the importance of consistency month to month, and reiterate that we are interested in the information you
can provide with relative ease. Some specific (ideal) considerations include:• Include only group term life business. Exclude any GUL/GVUL, COLI/BOLI, 10/20-year group term, etc.
• Include or exclude premium for accident riders depending on how they are handled in your system; just be
consistent and identify what is included.
• Include both self-administered and list-billed business.
• For exposed lives, we recognize that some data (list billed groups, for example) may be more current andaccurate than other data. Please provide your best representation of exposed lives, and identify any
particular limitations or special considerations in your submission.
Final Notes on Requested Data
We intend to turn around results rapidly to maximize value on internal decision-making for participating carriers.
With that in mind, we have tried to keep the request as simple as possible. We have tried to define exactly what weare requesting, but if your own tracking does not align and the customization is difficult, then please provide what
you normally track rather than trying to match our definitions. The period-over-period change will be most valuable,

Copyright © 2023 Society of Actuaries Research Institute61

so consistency is more important than precise definitions. We understand there can be nuances in how carrierscount claims and track exposures, but we think the recently observed changes will be valuable. If you have any
questions at all about what we are asking, please reach out.
PLEASE NOTE: YOUR DATA SUBMISSIONS SHOULD NOT CONTAIN ANY INDIVIDUAL POLICY LEVEL INFORMATION.
PLEASE SEND ONLY THE AGGREGATED SUMMARY INFORMATION REQUESTED.
SOA staff will be receiving and compiling your submissions and the SOA is not able to receive any personal
information on your policyholders.
Reports
Our minimal request is for the monthly results without industry, geographic, or demographic segmentation. Pleaseprovide the additional segment data as you are able, and we will return cross-industry information consistent withyour submission. We do not plan to provide individual carrier-level experience.
We plan to show cross-industry extra mortality by calendar month. We will compare the most recent months to theprior periods, including prior months, and the same month a year ago.
We will not show individual carrier experience, but may comment on the consistencies of changes across carriers.
Technical Notes
The accompanying Excel workbook contains specific templates for the data submission. You can use the Excel
templates or submit data in a format of your choosing. The workbook includes an “Outline” tab to guide yoursubmission.
Please return the submission via e-mail to Korrel Crawford at kcrawford@soa.org. If you have concerns about filesecurity, please contact her and she will provide you with an alternate means of submitting data in a more secure
fashion.

Copyright © 2023 Society of Actuaries Research Institute

62

Appendix B: Geography and Industry Code Mappings
Table B.1

GEOGRAPHY CODE MAPPINGS
Abbreviation

State/Province Name

Division

RegionAA

U.S. Armed Forces–Americas

Division 11: Unknown

Other

AB

Alberta

Division 10: Canada

Other

AE

U.S. Armed Forces–Europe

Division 11: Unknown

Other

AK

AlaskaDivision 09: Pacific

West

AL

AlabamaDivision 06: East South Central

Southeast

AP

U.S. Armed Forces–Pacific

Division 11: Unknown

Other

AR

Arkansas

Division 07: West South Central

SoutheastAS

American Samoa

Division 09: Pacific

Other

AZ

Arizona

Division 08: Mountain

West

BC

British Columbia

Division 10: Canada

Other

CA

California

Division 09: Pacific

West

CO

Colorado

Division 08: Mountain

West

CT

Connecticut

Division 01A: Southern New England

Northeast

DC

District of Columbia

Division 02: Middle Atlantic

Northeast

DE

DelawareDivision 02: Middle Atlantic

NortheastFL

FloridaDivision 05: South Atlantic

SoutheastFM

Micronesia

Division 09: Pacific

Other

GA

Georgia

Division 05: South Atlantic

Southeast

GU

Guam

Division 09: Pacific

Other

HI

Hawaii

Division 09: Pacific

West

IA

Iowa

Division 04: North Central

MidwestID

Idaho

Division 08: Mountain

West

IL

Illinois

Division 03: Great Lakes

MidwestIN

Indiana

Division 03: Great Lakes

MidwestKS

KansasDivision 04: North Central

MidwestKY

KentuckyDivision 06: East South Central

Southeast

LALouisiana

Division 07: West South Central

SoutheastMA

Massachusetts

Division 01A: Southern New England

Northeast

MB

Manitoba

Division 10: Canada

Other

MD

MarylandDivision 02: Middle Atlantic

Northeast

ME

Maine

Division 01B: Northern New England

NortheastMH

Marshall Islands

Division 09: Pacific

Other

MI

Michigan

Division 03: Great Lakes

MidwestMN

Minnesota

Division 04: North Central

MidwestMO

Missouri

Division 04: North Central

MidwestMP

Northern Mariana Islands

Division 09: Pacific

Other

MS

Mississippi

Division 06: East South Central

Southeast

MT

Montana

Division 08: MountainWest

Copyright © 2023 Society of Actuaries Research Institute63

Abbreviation

State/Province Name

Division

RegionNB

New Brunswick

Division 10: Canada

Other

NC

North Carolina

Division 05: South Atlantic

Southeast

ND

North Dakota

Division 04: North Central

MidwestNE

Nebraska

Division 04: North Central

MidwestNH

New Hampshire

Division 01B: Northern New England

Northeast

NJ

New Jersey

Division 02: Middle Atlantic

Northeast

NL

Newfoundland and Labrador

Division 10: Canada

Other

NM

New Mexico

Division 08: Mountain

West

NS

Nova Scotia

Division 10: Canada

Other

NU

Nunavut

Division 10: Canada

Other

NV

NevadaDivision 08: Mountain

West

NW

Northwest Territories

Division 10: Canada

Other

NY

New York

Division 02: Middle Atlantic

Northeast

OH

Ohio

Division 03: Great Lakes

MidwestOK

Oklahoma

Division 07: West South Central

Southeast

ON

Ontario

Division 10: Canada

Other

OR

OregonDivision 09: Pacific

West

Other

Other

Division 11: Unknown

Other

PA

Pennsylvania

Division 02: Middle Atlantic

NortheastPE

Prince Edward Island

Division 10: Canada

Other

PR

Puerto Rico

Division 05: South Atlantic

Other

PW

Palau

Division 09: Pacific

Other

QC

QuebecDivision 10: Canada

Other

RI

Rhode Island

Division 01A: Southern New England

Northeast

SC

South Carolina

Division 05: South Atlantic

Southeast

SD

South Dakota

Division 04: North Central

MidwestSK

Saskatchewan

Division 10: Canada

Other

TN

Tennessee

Division 06: East South Central

Southeast

TX

Texas

Division 07: West South Central

SoutheastUN

Unknown

Division 11: Unknown

Other

Unknown

Unknown

Division 11: Unknown

Other

UT

Utah

Division 08: Mountain

West

VA

Virginia

Division 05: South Atlantic

Southeast

VI

U.S. Virgin Islands

Division 05: South Atlantic

Other

VT

Vermont

Division 01B: Northern New England

Northeast

WA

Washington

Division 09: Pacific

West

WI

Wisconsin

Division 03: Great Lakes

MidwestWVWest Virginia

Division 02: Middle Atlantic

Northeast

WY

Wyoming

Division 08: Mountain

West

YK

Yukon

Division 10: Canada

Other

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Table B.2

INDUSTRY CODE MAPPINGS
Two-Digit
Standard
Industrial CodeIndustry Group

Collar Color

00

Unknown/Invalid

Unknown01

Agricultural; Forestry; Fishing

Blue

02

Agricultural; Forestry; Fishing

Blue

03

Agricultural; Forestry; Fishing

Blue

04

Agricultural; Forestry; Fishing

Blue

05

Agricultural; Forestry; Fishing

Blue

07

Agricultural; Forestry; Fishing

Blue

08

Agricultural; Forestry; Fishing

Blue

09

Agricultural; Forestry; Fishing

Blue

10

MiningBlue

11

MiningBlue

12

MiningBlue

13

MiningBlue

14

MiningBlue

15

Construction

Blue

16

Construction

Blue

17

Construction

Blue

18

Construction

Blue

19

Construction

Blue

20

Manufacturing—Food

Blue

21

Manufacturing—Food

Blue

22

Manufacturing—Clothes; Textile; Wood

Blue

23

Manufacturing—Clothes; Textile; Wood

Blue

24

Manufacturing—Clothes; Textile; Wood

Blue

25

Manufacturing—Clothes; Textile; Wood

Blue

26

Manufacturing—Clothes; Textile; Wood

Blue

27

Manufacturing—Paper; Drugs

Gray

28

Manufacturing—Paper; Drugs

Gray

29

Manufacturing—Paper; Drugs

Gray

30

Manufacturing—Paper; Drugs

Gray

31

Manufacturing—Paper; Drugs

Gray

32

Manufacturing—Paper; Drugs

Gray

33

Manufacturing—Heavy; Steel

Blue

34

Manufacturing—Heavy; Steel

Blue

35

Manufacturing—Heavy; Steel

Blue

36

Manufacturing—Heavy; Steel

Blue

37

Manufacturing—Auto, Airplanes, Precision Equipment

Blue

38

Manufacturing—Auto, Airplanes, Precision Equipment

Blue

39

Manufacturing—Auto, Airplanes, Precision Equipment

Blue

Copyright © 2023 Society of Actuaries Research Institute65

Two-Digit
Standard
Industrial CodeIndustry Group

Collar Color

40

Transport; Communication; Utilities

Blue

41

Transport; Communication; Utilities

Blue

42

Transport; Communication; Utilities

Blue

43

Transport; Communication; Utilities

Blue

44

Transport; Communication; Utilities

Blue

45

Transport; Communication; Utilities

Blue

46

Transport; Communication; Utilities

Blue

47

Transport; Communication; Utilities

Blue

48

Transport; Communication; Utilities

Blue

49

Transport; Communication; Utilities

Blue

50

Wholesale Trade

Gray

51

Wholesale Trade

Gray

52

Retail—Trade

Gray

53

Retail—Trade

Gray

54

Retail—Trade

Gray

55

Retail—Trade

Gray

56

Retail—Trade

Gray

57

Retail—Trade

Gray

58

Retail—Trade

Gray

59

Retail—Trade

Gray

60

Banks and Securities

White

61

Banks and Securities

White

62

Banks and Securities

White

63

Insurance; Other Finance

White

64

Insurance; Other Finance

White

65

Insurance; Other Finance

White

66

Insurance; Other Finance

White

67

Insurance; Other Finance

White

68

Insurance; Other Finance

White

69

Insurance; Other Finance

White

70

Hotels/Personal Services

Grey

71

Hotels/Personal Services

Grey

72

Hotels/Personal Services

Grey

73

Misc. Service/Data Processing

Grey

74

Misc. Service/Data Processing

Gray

75

Misc. Service/Data Processing

Gray

76

Misc. Service/Data Processing

Gray

78

Misc. Service/Data Processing

Gray

79
80

Misc. Service/Data Processing
Doctors’ Offices

Gray
White

81

Legal Services

White

Copyright © 2023 Society of Actuaries Research Institute66

Two-Digit
Standard
Industrial Code82

Industry Group

Collar Color

Educational Services

White

83

Social Services

White

84

Museums and Membership Organizations

White

85

Museums and Membership Organizations

White

86

Museums and Membership Organizations

White

87

Engineering, Architecture, Business Consulting

White

88

Engineering, Architecture, Business Consulting

White

89

Engineering, Architecture, Business Consulting

White

90

Public Administration

White

91

Public Administration

White

92

Public Administration

White

93

Public Administration

White

94

Public Administration

White

95

Public Administration

White

96

Public Administration

White

97

Public Administration

White

99

Unknown/Invalid

Unknown

Unknown

Unknown/Invalid

Unknown

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67

Appendix C: Survey Methodology and Documentation
C.1 DOCUMENTATION
Participating companies provided both claims and exposure data on a monthly basis. The initial data request can befound in Appendix A. For claims information, the following fields were requested:
•
•
•
•
•
•

Incurred Month
Reported Month
Product Type
Cause of Death
Number of Claims
Total Claim Amount Covered/Paid

For exposure information, the following fields were requested:••••

Exposure Month
Product Type
Exposed Premium
Number of Inforce Lives

In addition to the above “core” request, participants were also optionally asked to provide the above information
split by state, age/sex grouping and industry (two-digit SIC code). The lone exception is that Reported Month was
not requested for the claims portion of these three more granular cuts of the data.
Below is a summary of the key processing assumptions and decisions for each of these fields.
Claims–Incurred Month
Incurred Months were generally used as provided without adjustment. The primary exception was thatdata with an Incurred Month after the as-of-date were excluded. For example, for the December 2022 datasubmissions, claims with an Incurred Month of January 2023 were excluded.
Claims–Reported Month
Claims with a Reported Month before the Incurred Month were adjusted by setting the Reported Monthequal to the Incurred Month.
Claims–Product Type
Carriers were asked to provide data with one of three Product Types: Employee Basic, Employee
Supplemental/Voluntary and Retiree Life. All alternative codes received for the Product Type field weresent as data questions to carriers and ultimately mapped to one of these three principal product types.
Notably, dependent claims were mapped to one of the two employee types, depending on the code
received.
Claims–Cause of Death

Copyright © 2023 Society of Actuaries Research Institute68

Contributors were asked to identify claims as due to one of the 15 cause of death groupings shown inAppendix E.
Claims–Number of Claims and Total Claim Amount Covered/Paid
Claims by Reported Date were processed as is without adjustment. However, on an incurred basis, theclaims needed to be adjusted with completion factors as described in Section C.2.1; otherwise, theincidence rates in recent periods would be understated.
Exposure–Exposure Month and Product Type
Processing for these fields was analogous to the corresponding claims fields.
Exposure–Exposed Premium
The proximity of the survey request to the reporting dates of the data requested presented somechallenges in the monthly collection process because recent exposure data may be unavailable. For
example, one carrier indicated that their premium information for December 2022 was incomplete;therefore, the average premiums for July through September 2022 were imputed for December 2022 forthis carrier.
Exposure–Number of Inforce Lives
Not all carriers provided the Number of Inforce Lives. For these carriers, this field was imputed using the
average premium per life (PPL) from carriers that supplied both premiums and lives. A separate PPL was
calculated for each year and product type, and the missing Number of Inforce Lives was populated by
dividing the provided premium by the PPL appropriate to the year and product type for which the premium
was earned. The Committee acknowledges that PPL varies by company and that the exposure completion
methodology may result in an aggregate incidence rate that differs materially from the actual level ofincidence, but the Committee does not expect that it distorted the trends monitored in this study.
Segment Information–State CodeState codes that did not match a listing of valid U.S. state, U.S. overseas territory or Canadian province
codes were sent as data questions to the contributors. Some records with indeterminate codes after thisquestioning process were mapped to an “unknown” category.
Segment Information–Age and Sex
Companies provided age information according to the following categories: 0–24, 25–34, 35–44, 45–54,
55–64, 65–74, 75–84 and 85+. These age groupings were then lumped into the following broader
groupings: 0–44, 45–64 and 65+. Sex information was collected as male, female and unknown.
Segment Information–Industry
For the Industry field, contributors were asked to provide two-digit SIC codes. Codes that did not match alist of valid two-digit SIC codes were sent as data questions to the contributor for resolution. Some records
with indeterminate codes after this questioning process were mapped to an “Unknown” category.

Copyright © 2023 Society of Actuaries Research Institute69

C.2 RESULTS PROCESSING AND REVIEW
C.2.1 COMPLETION OF CLAIMSA table of claim counts by Incurred Month and Reported Month was compiled to develop completion factors.
Month-to-month completion factors were estimated using the accumulated totals for a particular incurred month inconsecutive reported months. Some seasonal variation was observed in the completion factors, so adjustments tothe factors for calendar month were incorporated.
The total completion factors were computed by cumulatively applying the month-to-month completion factors to all
subsequent months. For example, the total completion factor for a claim in month 0 is the factor for month 0 to 1,
times the factor for month 1 to 2, times the factor for month 2 to 3, and so forth. In total, 36 months of completion
were used.
Completion factors vary by calendar month, reflecting the seasonal nature of claim reporting and claim processing
speeds. The Committee also incorporated factor variation by reporting speed groups. The rate at which thecontributing companies’ claims were completed was analyzed and categorized into five groups, with three to fivecompanies in each reporting speed group.

C.2.2 BROADER CLASSIFICATION OF SEGMENT INFORMATIONFor credibility and confidentiality reasons, the industry codes and state codes were grouped into broader segments
for analysis. State codes were mapped to one of 11 divisions, with the New England division split into northern andsouthern portions. The state codes were also mapped to four broader U.S. regions (Northeast, Midwest, Southeast,West), with Canada, overseas territories and unknown codes grouped into a fifth “Other” region.
The two-digit SIC codes were organized into 23 different groupings, and then more broadly into one of four codes
by collar color (White, Gray, Blue, Unknown).
A table showing the details of these mappings can be found in Appendix B.

C.2.3 UNKNOWN CLAIM DIAGNOSISThe Unknown claim diagnosis category is artificially large for September 2022 through December 2022. This is
primarily because of the newness of these claims and a reflection of the claim adjudication lifecycle. It is notuncommon to find an additional time lag between the claim reporting date and the point in the claim adjudication
process when the COD is known, allowing for the claim to be categorized. As claims data have been collected andrefreshed each month, the Committee has observed that the concentration of claims with an unknown COD
decreases as the number of months between the original reporting date and the data collection date increases.

C.2.4 COVID-19 CLAIMS FROM 2019 OR EARLIER
The data show a handful of COVID-19 claims with dates of death in 2019 or earlier. The Committee believes thatthese are coding errors where incorrect COD codes were supplied. These claims remain in the data as submitted
without adjustment.

C.2.5 GROUPINGS BY COMPANY SIZETo review results by company size (see Section 5.4), contributors were split into three groups based on annualized
premium amounts from 2019. The Small group consists of companies with less than $300 million in 2019 premiums,
the Medium group consists of companies with between $300 million and $1 billion, and the Large group consists of

Copyright © 2023 Society of Actuaries Research Institute70

companies with more than $1 billion. The breakpoints were chosen to ensure at least six companies in each group.
The Small group contains six companies, and the Medium and Large groups contain seven companies each.

Copyright © 2023 Society of Actuaries Research Institute

71

Appendix D: Completion Factor Development
D.1 BY CLAIM COUNT
Historic Group Life claim reporting patterns by claim count have been studied to develop completion factors, whichwere then used to translate reported claims through August 2020 by incurral month into estimated ultimate
incurred claims for each month. The completion factors for this report are based on the total set of claims by allcauses from all 20 participating carriers, with incurred dates of January 2017 or later and reported dates up throughSeptember 2020. Since that time, completion factors have been reviewed periodically, and no changes were madeto them.
Claims were batched into a claim triangle with incurred month on the horizontal axis and reported month on thevertical axis. Lag is defined as the number of months between when a death occurs and when the claim is reported
to a carrier. Thus, a death that was both incurred and reported in August 2020 would have a lag of zero, whereas adeath incurred in June 2020 but reported in August 2020 would have a lag of two, and so on. A subset of the claim
triangle is displayed in Table D.1.
Table D.1

2020 INCURRED CLAIMS BY INCURRED MONTH AND REPORTING LAG
Months ofReporting Lag
0
1
2
3
4
5
6
7

Jan. 2020
11,887
14,647
5,822
2,159
1,350
910
559
438

Feb.
2020
10,137
14,412
4,961
1,867
1,242
623
374

Mar.
2020
10,932
15,443
5,713
2,656
1,283
732

Incurred Month
Apr.
May
2020
2020
13,971
11,276
16,55916,158
6,916
6,109
2,785
2,249
1,386

June
2020
10,786
14,850
5,517

July 2020
13,014
15,686Aug.
2020
12,826

Month-to-month completion factors were developed using the accumulated totals for a particular incurred monthin consecutive reported months. Seasonal variations were observed during the first two months of lag, so
adjustments to the factors for calendar month were incorporated. The total completion factors, as displayed inTable D.2, were computed by cumulatively applying the month-to-month completion factors to all subsequentmonths. The data presented in both Tables D.1 and D.2 have not been changed since the July 2021 publication ofthis report.

Copyright © 2023 Society of Actuaries Research Institute72

Table D.2

ESTIMATED COMPLETION FACTORS BY NUMBER OF MONTHS OF LAG AND CALENDAR MONTH
Lag
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35

Jan.
3.55941.48081.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Feb.
3.7656
1.4313
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Mar.
3.44051.4313
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Apr.
3.44051.4313
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006May
3.44051.4313
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006June
3.44051.4313
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006July
3.33871.38901.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Aug.
3.11291.4313
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Sep.
3.33871.38901.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Oct.
3.2384
1.4313
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Nov.
3.55941.48081.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006Dec.
4.01501.4313
1.1752
1.10151.06971.05301.04301.03631.0314
1.02771.02481.02211.01971.01771.0162
1.01481.01361.01261.01161.01071.00981.00901.0083
1.00761.00691.0062
1.00561.00511.00461.0042
1.00381.00331.00301.00251.00221.0006

Copyright © 2023 Society of Actuaries Research Institute73

D.2 BY FACE AMOUNTOur analysis showed that larger face amount claims report faster than lower face amount claims. Thus, over time
the average face amount for an incurral month decreases as claims continue to be reported in later months. For
example, the average face amount of claims reported in the first month of an incurral period may be $40,000, butthree years later, it may be $36,000. This would imply that an adjustment factor of 90% is needed to moreaccurately complete the total claim amounts.
The development of average claim amounts over time was studied from 2017 to 2019 for each month, and a set offactors were developed to adjust the projected claim amounts in future reports. Table D.3 shows a summarizedversion of the resulting adjustment factors. These adjustment factors have since been incorporated into thecompletion factors used within this report.
Table D.3

AVERAGE CLAIM AMOUNT ADJUSTMENT FACTORS BY REPORTING LAG MONTH (ILLUSTRATIVE)
Reporting Lag Month
0
1
2
3
10
20
35

Adjustment to Average Size
86.0%
92.7%
95.8%
97.2%
99.1%
99.7%
100.0%

D.3 BY CAUSE OF DEATH
It was unknown early in the pandemic whether COVID-19 claims would be reported more quickly or slowly thanother claims. Assignment of the COD is typically later in the claim adjudication cycle then reporting of the claim, so
COVID claims in general were expected to complete a bit more slowly than average claims because of the need tocomplete that step in the adjudication cycle. For deaths in June 2020 through February 2021, it appears that COVID19 claims were being reported at roughly the same rate as the non-COVID-19 set of claims (see Table D.4). The
Committee has reviewed the relative reporting speed of COVID-19 claims at multiple intervals during the pandemic
and has concluded that it is not materially different than average; for this reason, the analysis has not been revisitedfor this report.
Table D.4

CHAIN-LINK FACTORS FOR DEATHS IN JUNE 2020–FEBRUARY 2021
Lag Months
0
1
2
3
0–3

COVID

All Other Causes

COVID/All Other Causes

2.188
1.203
1.062
1.031
2.888

2.202
1.198
1.068
1.034
2.916

99.3%
100.4%
99.4%
99.7%
99.1%

Copyright © 2023 Society of Actuaries Research Institute74

D.4 BY COMPANY REPORTING SPEED
The Committee observed that incurred claim completion rates vary significantly from company to company. Upon
analyzing the differences, the 20 contributing companies were grouped into five “reporting speed” groups based on
similar reporting patterns. The completion ratios were studied from 2017 through 2020 for these five groups, butmore significant weight was placed on data from 2020 as was the case for the base completion factor development.
The completion patterns for the five groups were compared to the aggregate completion factors and expressed as
adjustments in Table D.5. The Committee observed that the differential in completion time was material for the firstsix reporting months for each incurred period. Further, the Committee did not discern any credible difference in the
speed by incurral calendar month; hence only one vector of adjustments is provided for each group. These
adjustments provide a more representative picture for the individual company reports and, to a lesser extent,
improve the predictive fit of completed claims in total. Thus, the current speed group factors have been updated ascompared to Section 9.3 of the December 2020 publication.
Table D.5

COMPLETION ADJUSTMENT FACTORS BY REPORTING SPEED GROUP
LagGroup 1

Group 2

Group 3

Group 4

Group 5Aggregate

0
1
2
3
4
5

64.8%
86.1%
94.3%
96.9%
98.0%
98.5%

81.6%
94.6%
98.5%
99.3%
99.6%
99.8%

111.2%
100.7%
100.5%
100.3%
100.2%
100.1%

122.0%
101.4%
100.9%
100.7%
100.5%
100.4%

250.0%
125.7%
107.1%
103.7%
102.5%
101.9%

100.0%
100.0%
100.0%
100.0%
100.0%
100.0%

Groups 1 and 2 reported claims faster than the aggregate completion factors, evidenced by reducing the magnitude
of completion factors for the first six months of reporting. Groups 3 through 5 reported claims slower than theaggregate completion factors.

Copyright © 2023 Society of Actuaries Research Institute

75

Appendix E: Cause of Death Mapping
Table E.1

CAUSE OF DEATH MAPPING
COD Group
No.
1
2
3

4

Group Name

ICD10 Codes

ICD-9 Codes

CancerDiabetes
Influenza andPneumonia
Major
Cardiovascular
Diseases

C00–C97
E10–E14140–239
249–250
480–488 (pneumonia and influenza) or
487–488 (just influenza)

5

COVID-19

6

Accidents (Motor
Vehicle)7

Accidents (Non–Motor Vehicle)

8910

Suicide
Homicide
Liver

11

Drug Overdose

12
13
14
15

All Other/
Unknown
Respiratory
Cerebrovascular,
Including Stroke
Alzheimer’s

J09–J18

I00–I09, I11, I13, I20–I51
U07.1, U07.2, B97.29, B97.26, Z03.818,
Z20.828, Underlying Cause of Death
V02–V04, V09.0, V09.2, V12–V14, V19.0–
V19.2, V19.4–V19.6, V20–V79, V80.3–
V80.5, V81.0–V81.1, V82.0–V82.1, V83–
V86, V87.0–V87.8, V88.0–V88.8, V89.0,
V89.2
W00–X59, Y86, V01, V05–V06, V09.1,
V09.3–V09.9, V10–V11, V15–V18, V19.3,
V19.8–V19.9, V80.0–V80.2, V80.6–V80.9,
V81.2–V81.9, V82.2–V82.9, V87.9, V88.9,
V89.1, V89.3, V89.9, V90–V99, Y85
U03, X60–X84, Y87.0
U01–U02, X85–Y09, Y87.1
K70, K73–K74
This is a subset of accident, assault, suicide
and undetermined and requires more thanthe primary COD to identify: X40–44, X60–
64, X85 or Y10–Y14 in combination with anyof the following multiple COD codes: T40.9,
T40.1, T40.2, T40.3, T40.4 or T40.6

393–429

Not applicable

E810–E829

Subset of 800–959 and 978–999, alongwith supplemental E-codes

E950–E959
E960–E969
570–573

960–977 and E930–E949

J00–J08, J19–J98

All claims/codes not in groups 1–11 or
13—15
460–479 and 489-–519

I60–I69G30

430–438 and V12.54
331

All claims not in groups 1–11 or 13–15

Copyright © 2023 Society of Actuaries Research Institute76

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