no one is there to hear it fall?" The answer depends upon our objective -- do we wish to know the rate at
which trees are falling, or do we wish to know how many falling trees are heard.

Extending this question to the assessment of roof-fall injuries in a mine, one should consider a number
of factors. For example, when and where in the mine and at what frequency do we have roof falls. How
many workers are going to be subjected to the roof-fall (not every miner may be exposed to the event), and
finally what is the probability that an exposed worker will be injured or killed.

Surveillance and Other Factors

The above discussions dealt with quantities that relate to degree of hazard, but there are also economic,
and social concerns which impact directly on individual workers, groups of workers, the work place, the
industry, and to society in general. For example, with regard to economics, one can refer to the recent
NORA document which states -- "1994 occupational injuries alone cost $121 billion in lost wages and
productivity, administrative expenses, health care and other costs". -- This economic impact (about
$16,000/occupational injury) as well as other impacts (hazards and societal) need to be considered in the
assessment of risks, but often it is uncertain as to how to quantify them.

If one interprets the ‘numerator’ of surveillance rate data as referring to those individuals, institutions
and events which are directly affected by work place injuries, then weighting factors that would relate to the
numerator (referred to as N-factors) might be described as

Numerator or N-factors
1. Hazard Impact -- the actual number of workers injured and the degree of injury.

2. Economic Impact -- the direct costs of the accident to industry, government, and injured party and
family in terms of medical expenses, compensations, entitlements, worker replacement, and
business loss.

3. Societal Impact -- the direct impact of the accident to the injured party, his/her family, and fellow
employees in terms of anguish, grief, social concerns, mental and physical health,

The 'denominator' of surveillance data can then be interpreted as referring to those individuals,
institutions and events which are in harms way, i.e., those who will be affected by future accidents. The
denominator weighting factors (D-factors) may or may not cancel out the N-factors during normalization of
the surveillance data. However, the reliability of the normalized surveillance data will depend equally on the
reliability of the data making up both the N- and D-factors.

Denominator or D-factors

1. Hazard Impact -- the actual number of workers exposed to a specific traumatic injury (e.g., an
underground mine explosion may expose all underground workers to fatal injury, but not those
personnel who work above ground), the probability of worker injury or fatality, and the frequency
of mishaps that might cause injury


Somewhat akin to the above findings is the data reported by Frost, Frank and Maibach (10) which
indicates that news media coverage does not correlate with risk of dying (mortality). Using an approach
similar to that described above, but with different news publications and methods of measurement, national
news media coverage was characterized for 11 different categories of cause of death for the year 1990 -
ranging from heart disease and malignancy to trauma such as homicide and unintentional (figure 7).
Homicide, with a lowest mortality as a cause of death, was found to be of greatest concern to the exposed
American public (a D-factor) -- greater than heart attack (highest mortality), by about a factor of 20. The
results indicate that there is less news coverage in the case of causes of death which most people eventually
die of, i.e., when you get old (malignancy may be an exception). On the other hand, news media coverage
appears to be greatest for those causes of death which involve a younger exposed population, i.e., those at
an age not normally expected to die. A ranking of mortality risk taking into account age or lifetime lost
(e.g., reference 11) might result in a closer correlation between news media coverage and risk of dying.

Relative Rankin
Amer.J.Public Health, v.87, 842-845, 1997

a)
© 1 homocide
O09 2. unintentional
Gog 3. hiv
E -_ 4 liver
6 0.7 5 malignancy
£06 8 suicide
7 copd

20S 8 pneumonia
X 0.4 9 diabeles
5 10 heart

0.3
C 11 cerbrovescular
vo 0.2
2 1
3 0.
® 0+
a

1 2 3 4 5 6 7 8 9 10 11
Cause of Death

MM: foto! | medio cover /# fatal

Figure 7. Relative rankings of causes of death by fatalities and by news media coverage.

Summary

The NIOSH surveillance model of risk assessment tends to be concerned with evaluating in great detail
the number of people killed (the numerator part of the fatality rate), while the evaluation of those factors
which refer to the people exposed (the denominator of the fatality rate) are given much less attention. Yet,

the numeric values assigned to the numerator and denominator contribute equally to the value of a risk
factor.


In another surveillance study, this time by the U.S. Bureau of Mines utilizing MSHA data (7), it was
reported that the annual rates for coal mining, expressed as fatalities per 200,000 employee-hours of
exposure (determined over a three year period) decreased with both increasing mine size and time over the
decade of 1980 and 1990 (figure 3). However, the sum of fatal and permanent disability injuries
apparently did not change over the decade period. This suggests that the number of events causing
traumatic injury might not have changed over ten years, but the types of injury did (e.g., swapping
disabling incidents for fatal incidents). In other words, mining was made less hazardous over the ten year
period, but not necessarily safer in terms of frequency of injury events. When all the incidents of death,
permanent injury and serious injury as reported in reference 7 are considered, the relative risk of injury
actually appears to be independent of mine size (figure 4), however, the degrees of hazard apparently do
change.

5
8g Underground Mine Injuries (1989-91)
a RH. Peters and 8. Folta (1994)
o
6
a
£
5
©
S
oe
a
£3
c
22
3}
°
a1
3
8 S
nO TM
L 1-20 21-50 51-100 >100 Overall
8 Number of employees in mine
©
3 (7) fetal HB perm. disoble serious injury
«

Figure 4. Risk factors for injury in coal mines of various size (1994).

To reconcile the various factors that relate to risk of injury, it is necessary to be concerned (at least in
part) with the degree of safety of the work place itself as well as the safety of the work place/worker
interface. Namely, that there are a number of events which can occur in the work place, any one of which
could lead to worker injury, but only under the "wrong" circumstance. The "wrong" circumstance would
occur when there is a worker present at the time of the event. If present during the event, one should then
consider what is the chance that he/she would be injured, and to what extent.

A roof-fall in a mine is certainly an event that can cause death and injury to workers, but only when
miners are under the roof at the time of the event. The extent of injury to a miner then depends on what
part of his/her body was under the roof when it falls. That is, the number of reported injuries by itself does
not necessarily define the number of incidents that can lead to injury nor does it define the hazards of the
work place. This is somewhat akin to the oft-asked question: "a tree falls in the forest, does it make noise if


2. Economic Impact -- the cost to workers, industry and the government for improvements in safety
and worker protection. For example, increased liability insurance, medical premiums, and health
and safety expenditures, worker job loss and financial business loss in the event of industry
closure*.

3. Societal Impact -- the impact of the event on the public, government agencies, workers and
industry. Public attention to traumatic injuries (e.g., news media coverage) can lead to significant
social consequences, such as alteration of work procedures and techniques, new safety regulations,
and changes in safety and health research priorities and funding. This has been delineated by J.
M. Bronstein (8) in a discussion of the role of societal impact in the formulation of worker safety
regulations as related to the health hazards of dust in coal mines and cotton mills.

The congressional legislation to create the U.S. Bureau of mines in 1910 and to enact the Coal Mine
Health and Safety Act of 1969, was a societal response to major mine disasters involving mine gas/dust
explosions. The Occupational Safety and Health Act of 1970 forming OSHA and NIOSH was due to
growing concerns for the safety of all workers in the U.S.

Evaluating Societal Impact

One method of evaluating societal impact would be to poll the various segments of our society as to
their thoughts on a given question (e.g., TV ratings). Another method might be to examine what the
newspapers say about the question (e.g., political ratings). If we assume that the news media coverage is a
reasonable surrogate for public opinion which in turn will lead to societal impact, then societal impact of
industrial accidents might be evaluated through the attention that newspapers give to each accident. Almost
all newspapers currently maintain electronic files which can be searched rapidly, and using information
retrieval services, news articles can be readily recovered.

The author undertook this approach for coal mine fatalities in the year 1992. This year was late enough
to be within the full electronic data coverage, and a coal mine disaster did occur in 1992. A database
program called DIALOG (9) was utilized since it was readily available. In proceeding with the test, MSHA
supplied a list of coal mine fatalities for 1992, which included coded information on about 38 data
categories, describing the fatal event. The victims’ name along with 'MINE ACCIDENT ' served as the
primary key words for the search.

There were 8 categorics of 'cause of fatality’ listed for 1992, involving 35 separate fatal incidents and a
total of 46 fatalities. All except 3 of the incidents resulted in single fatalities. The news coverage data are
depicted as bar graphs in figures 5 and 6. In terms of the relationship between cause of death and news
coverage, it is clear that ‘EXPLOSION ' results in far greater news coverage than all of the other cause of
death categories combined -- about a factor of ten greater than 'FALL OF ROOF’, even though almost the
same number of fatalities occurred in both categories. Figure 6 depicts the societal impact of multiple

?The 1990 Mathies underground coal mine fire (near Pittsburgh, PA), resulted in no injuries or fatalities,
but did lead to about $100 million loss in equipment and property (an N-factor), and the loss of 410 jobs
when the mine was sealed and closed down (a D-factor).


The N- and D-factors of risk are much more involved than simply the numbers of injured or exposed.
They involve economic, degree of hazard and societal impacts that should be considered in evaluating risk -
particularly for low frequency disaster-type events. These additional factors will relate differently to the
numerator and denominator of risk and hence can easily effect risk evaluations. This is particularly
important in the case of disasters where the evaluation of D-factors requires far greater attention than what
is currently being given in current risk analysis models. The importance of the D-factors becomes even

more apparent when it is realized that the exposed workers are the ones in harms way, and it is their health
and safety that needs to be protected.

References

1. W. Haddon, Jr., "Advances in the Epidemiology of Injuries as a Basis for Public Policy," Public Health
Reports, 95, 411-421 (1980).

2. A. Greife (column editor), "Hazard Surveillance: Its Role in Primary Prevention of Occupational
Disease and Injury," Appl. Occup. Environ. Hyg., 10, 737-742 (1995).

3. “National Occupational Research Agenda (NORA)," publication of the National Institute of
Occupational Safety and Health, Centers for Disease Control and Prevention, Public Health Service, U.S.
Department of Health and Human Services, (1996) 75 pp.

4. “Fatal Injuries to Workers in the U.S., 1980-1989: AW Decade of Surveillance," publication of the
National Institute of Occupational Safety and Health, Centers for Disease Control and Prevention, Public
Health Service, U.S. Department of Health and Human Services, (1993) 337 pp.

5. e.g. Bureau of Labor Statistics, Census of Occupational Fatalities and Injuries for 1993," Bulletin 2478.

6. e.g., U.S. Department of Labor, "Injury Experience in Coal Mining, 1990" MSHA Information Report
1205 (1991).

7. R.H. Peters and B. Fotta, "Statistical Profile of Accidents at Small Underground Coal Mines,"
Proceedings: Bureau of Mines Technology Transfer Seminar, Special Publication 18-94 (1994) pp 5-14

8. J. M. Bronstein, "The Political Symbolism of Occupational Health Risks", in The Social and Cultural
Construction of Risk," B. B. Johnson and V. T. Covello (eds.), Reidel Publishing Co., Boston (1987), pp
199-226,

9. DIALOG, a database search program copywriter Knight-Ridder Information, Inc. (1996),

10. K. Frost, E. Frank and E. Maibach, "Relative Risk in the News Media: A Quantification of
Misrepresentation", J. Amer. Public Health, 87, 842-845 (1997).

11. D. E. Fosbroke, S. M. Kisner and J. R. Myers, "Working Lifetime of Occupational Fatal Injury,"
Amer. J. Indust. Medicine, 31, 459-467 (1997).


SURVEILLANCE OF DISASTER--A VIEW FROM THE DENOMINATOR

Robert F, Chaiken
National Institute for Occupational Health and Safety
Pittsburgh Research Laboratory
P.O. Box 18070
Pittsburgh, PA 15236
412-892-6541 (Phone)
412-892-6891 (Fax)

Introduction

The National Institute of Occupational Safety and Health (NIOSH) is dedicated to achieving "safety
and health at work for all people -- through research and prevention." An important procedure in pursuing
this goal is the NIOSH surveillance studies where the number of injuries are monitored according to
demographic, employment, and injury characteristics. These numeric data are then used to identify injury
tisk factors, develop safety programs, and monitor implemented remediation methods. In essence, ongoing
surveillance data form the bases for directing the resources of NIOSH in setting of research and prevention
priorities, and in evaluating safety procedures.

This surveillance technique, which is based on the Public Health Service approach to identification and
control of disease (1, 2), has been used quite successfully in dealing with relatively high number injuries
such as hearing loss, musculoskeletal disorder, respiratory disorder, falls, etc. (3). However a problem
arises when extending this paradigm to lower frequency traumatic events; particularly those often referred
to as disasters (i.e., high impact events like mine explosions, airplane crashes, etc.). One can ask the
question - there hasn't been a coal mine fire fatality in the U.S. for over ten years, to what extent should we
be concerned with mine fire safety (resource-wise)? - The National Traumatic Occupational Fatalities
(NTOF) system (4) which NIOSH uses to survey occupational fatalities annually, would suggest that
underground mine fires would not be a high priority item in occupational safety. Yet, miners’ (i.¢., the
exposed workers) do consider mine fires and explosions to be major safety concerns.

I believe that we need to rethink our evaluation of work place disasters, what is worker exposure, and
what are the underlying assumptions (both explicit and implicit) as to the impact that economic, societal
and degree of hazard factors make on risk evaluation. The answers to all these problems, will require much
broader considerations than those in current surveillance safety and health models. This paper discusses
some facets of those considerations.

Surveillance and Hazard Factors

The problems referred to above can be elaborated on in terms of the ‘numerator’ and the ‘denominator’
of surveillance information, which generally involves a count of the injured or killed (in the numerator) as
normalized to some time interval and number of exposed workers (in the denominator). For example, the
NTOF surveillance system (4) evaluates the annual rates of fatalities per 100,000 workers for given
standardized categories (e.g., type of industry, cause of death, and other demographics). Similar
surveillance data for non-fatal injuries are classified by the U.S. Bureau of Labor Statistics (BLS) for all


fatality accidents. The words per fatality increase roughly exponentially with fatalities per incident. About
91% of the fatal incidents in 1992 involved single fatalities, accounting for 70% of all the fatalities. Yet
their societal impact in terms of news coverage accounted for only 7% of the words published. This is
probably similar to the societal impact of automobile crash fatalities as versus airplane crash fatalities.

News Maa Coverage (Soll tee!)
598 cor wee

Parates
6000 12
y CATEGORY
v EXP: EXPLOSION
A Aw FOF: FALL OF FACE °
E 4000 “nn Ww POW: POWER HAULAGE 3a é
g AW wy MAC: MACHERY &
Zz A a &
© 3000 ZN A ELE: ELECTRICAL o
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g Z A HI; HAND TOOLS, z
$ 2000 iy; AN le
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‘exp FOR

For POW MAC ELE PNR UT
oF

CAUSE OF DEATH CATEGORY

WM words ZZ) FATALS ERY EVENTS

Figure 5. News media coverage of underground coal mine fatalities (1992)

News Mudic Cover uga (Sociela trooct)
1997 coat Wie Favanies

8000 7 35

7000 4
6000
5000

4000

OL

30

25

20

3000

NO. OF EVENTS

2000

WORDS PER FATALITY

1000
ie)

8 4 2 1
NO. OF FATALS PER EVENT

i woros EVENTS.

Figure 6. News media coverage as a function of fatalities per event.


industries (5) and by the Mine Safety & Health Administration (MSHA) for mining (6)'. The NTOF rates
are often used for ranking the more hazardous industries and occupations, and for justifying specific
research programs.

Aside from the tacit assumption that every worker is exposed to every cause of injury, the rankings of
the NTOF risk factors assumes that risk based on fatality would correlate with the non-fatal risk factors --
an assumption that is apparently not always correct. This can be seen in figure 1 which depicts the relative
ranking of risk for fatal and non-fatal injuries in 1993 for 11 industry classifications. Here, the relative
rankings of the different industries are normalized to the highest value of risk in each category (i.e., fatal
and non-fatal). It is readily seen that the fatal and non-fatal risk factors do not necessarily correlate. Of
particular note is ‘manufacturing’, which ranks second in non-fatal injuries, but only fifth in fatal injuries,
and ‘mining’, which is first in fatality risk but only fifth in injury risk.

Relative Rankings (1993)
data from BLS and NIOSH
4

rank order for injury
”

ys aa — OM order for fatality

;
Z
)
Y
Y
y
Y
Z

Agric Mine "Const Manuf Trans Whole Retol Finan Serv
Industry

Relative Ranking
2

(Ziviury doto WM fatal dota

Figure 1. Relative ranking of risk factors for injury and fatality (1993).

This suggests that some degree of hazard factor should be considered when ranking occupational
injuries by industry. For example, these same data can be replotted as percent of injury leading to fatality,
which might be interpreted as a degree of hazard (figure 2). Here, the ‘agriculture’ and 'mining' industries
have almost an order of magnitude higher degree of hazard than the average for all industries - with
manufacturing being among the least hazardous (about one-half the average).

'The industrial classification 'mining' in the NTOF and BLS surveillance systems differs from that in the
MSHA system in that the former combine gas and oil industries with mining.


Fatal/ Non—Fatal Injuries (1993)
data from BLS and NIOSH

0.8
O71 numbers above bars ore value in %
075
0.66 Y Average (for all) = 0.087 %
0.64 Y
ro] 0.54
2
ie]
0.45
o
a 0.34
0.23 0.23
0.24
O14
0.05 0.04 9:95 0.04
0.03
5 LA wa WA WA. EA
Agric Mine Const Manuf Trans Whole Relol Finan Serv

0.5

0.3

0.2

0.1

Rate per 200, 000 employee-hrs exposur

Figure 3. Risk factors related to time period and size of coal mine.

Industry

Figure 2. Percent of traumatic injuries that are fatal.

Underground Mine Worker Injuries
R.H. Peters ond B. Fotta (1994)

'78-80
89-90
‘78-80 ‘89-90
: i ‘78-80 ‘89-90
1 to 50 21 lo 50 greoter than 50

Number of employees in mine

(7) total

HME perm. disoble