Abstract and Figures

Risk assessment is a key component of public health interventions intended to prevent or reduce adverse health effects. Health risk assessments are widely used to guide public health programming, as well as multi-sectoral studies of environmental impact and developmental decision making. Analytical risk assessment is a well-validated tool that is routinely used among certain subsets of public health, including those for chemical, radiological, and microbiological risk assessment. However, this is not the case for risk assessments involving disasters in general, or more specifically, for public health emergencies involving environmental hazards (eg, technological, hydro-meteorological, and seismic). There remains a need for a reproducible, well-validated, disaster-related health risk assessment process that is suitable for accommodating the current gaps in certainty. This report is intended to offer a practical framework and nomenclature for assessing disaster-related health risk that is: (1) accurate; (2) based upon historical evidence; (3) quantifiable in public health terms; and (4) inclusive of uncertainty. KeimM . Assessing disaster-related health risk: appraisal for prevention . Prehosp Disaster Med . 2018 ; 33 ( 3 ): 317 - 325 .
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Assessing Disaster-Related Health Risk:
Appraisal for Prevention
Mark Keim, MD, MBA
1,2,3,4
1. Disaster Doc, LLC, Atlanta, GA USA
2. National Center for Disaster Medicine and
Public Health, Bethesda, MD USA
3. Beth Israel Deaconess Medical Center,
Disaster Medicine Fellowship, Harvard
University Medical School, Boston MA
USA
4. Rollins School of Public Health, Emory
University Atlanta, GA USA
Correspondence:
Mark Keim, MD, MBA
DisasterDoc LLC
Atlanta, Georgia USA
E-mail: mark@disasterdoc.org
Abstract
Risk assessment is a key component of public health interventions intended to prevent or reduce
adverse health effects. Health risk assessments are widely used to guide public health pro-
gramming, as well as multi-sectoral studies of environmental impact and developmental decision
making. Analytical risk assessment is a well-validated tool that is routinely used among certain
subsets of public health, including those for chemical, radiological, and microbiological risk
assessment. However, this is not the case for risk assessments involving disasters in general, or
more specically, for public health emergencies involving environmental hazards (eg, techno-
logical, hydro-meteorological, and seismic).
There remains a need for a reproducible, well-validated, disaster-related health risk assessment
process that is suitable for accommodating the current gaps in certainty. This report is intended
to offer a practical framework and nomenclature for assessing disaster-related health risk that is:
(1) accurate; (2) based upon historical evidence; (3) quantiable in public health terms; and (4)
inclusive of uncertainty.
Keim M. Assessing disaster-related health risk: appraisal for prevention
Background
Problem Statement
While there are now multiple examples of qualitative and semi-quantitative assessments being
used for some degree of predicting disaster-related health risk, few models express health risk
in terms of the actual probability of health outcomes and uncertainty of evidence.
1
This is
particularly problematic since risk is denedastheprobabilitythataspecic outcome will
occur. This absence of metrics related to chance and uncertainty limit the utility of most public
health disaster risk assessments. This logically results in an acceptably accurate hazard iden-
tication and prioritization, but inaccurate and non-reproducible estimations of health-related
impact. This lack of information then complicates the ability to prioritize and allocate health
resources effectively, before and after the disaster.
Ideally, disaster risk management is based on a prioritization process. Once hazards
have been identied, they are assessed in terms of the probability and impact in terms of
losses. The hazards associated with the greatest probability and impact are prioritized. In
addition to prioritization, risk assessment also offers a process for ongoing research invol-
ving the interaction of health determinants, risk, and protective factors that may contribute
to future adverse health outcomes. Finally, risk assessment provides a framework for
monitoring and evaluating the performance of interventions intended to reduce adverse
health outcomes.
More recently, assessments of health risk have become an integral part of public health
and medical emergency preparedness programs.
2
One of the strengths of these assessments
lies in that these processes typically bring together multi-sectoral input for public health
decision making and plans. However, this diversity of input also creates challenges in
development of a standardized approach for assessment, as well as a common nomenclature
for assessing and communicating the characteristics of this risk.
The utility of existing models for risk assessment is attenuated by challenges with both
rst- and second-order uncertainty. This uncertainty is often due to a lack of predictability
(reected in the standard deviation) and accuracy (reected in the standard error) of results
from these assessments. Most risk assessment tools currently being used by the public
health and medical sectors lack predictive value that would guide accurate cost accounting
necessary for large-scale resource allocation or investment. Some apply risk-based
models that offer indices derived from semi-quantitative estimation of select disaster risk
Conicts of interest/funding/disclaimer: This
work was sponsored by DisasterDoc, LLC
(Atlanta, Georgia USA), a private consulting
rm specializing in disaster research and
education. The author attests that there are no
conicts of interest involved with the
authorship and publication of this work. The
material in this manuscript reects solely the
views of the author. It does not necessarily
reect the policies or recommendations of the
National Center for Disaster Medicine
(Bethesda, Maryland USA) or the Department
of Defense (Washington, DC USA).
Keywords: disaster; disaster risk; disaster risk
reduction; public health risk assessment; risk
assessment
Received: April 8, 2017
Revised: August 30, 2017
Accepted: September 24, 2017
doi:10.1017/S1049023X18000407
SPECIAL REPORT
Prehospital and Disaster Medicine
components (namely hazards, vulnerability, and capacity). Other
models offer retrospective analysis of the association between
disaster incidence and select risk factors (eg, social vulnerability
and capacity).
1,3-5
However, to date, risk assessments do not yet offer accurate
quantication of exposure as a risk factor for disaster-related
adverse health outcomes. To date, none are validated as predictive
of quantiable health risk. As a result, a relatively wide variety of
semi-quantitative risk assessments are being performed in various
locations throughout the US and the world. Measures in many of
these assessments are estimated subjectively and indicators are
often sufciently ambiguous so as to limit the reproducibility of
the assessment over time or among users. Few include quantiable
representations of uncertainty.
1
Clear denitions of terminology are essential to the perfor-
mance of a logical and evidence-based risk assessment. Lack of a
standardized nomenclature and approach has the potential to
increase variation in the accuracy and reproducibility of the
assessment (resulting in a second-order uncertainty).
Perhaps part of the justication for the current level of accep-
tance of these tools (known to be associated with relatively high
degree of uncertainty) may stem from the currently limited
applications of disaster risk assessments themselves. Typically,
disaster risk assessments are performed in order to gain a prior-
itized list of hazards before writing a plan that includes an all-
hazard approach to preparedness and response. Thus, much of the
value and time spent in prioritization of the risk is lost when this
level of specicity is not necessarily needed for plans involving risk
acceptance, which is largely comprised of general emergency
response functions, which are not hazard specic. On the contrary,
disaster risk management programs that include risk reduction
measures require hazard-specic risk prioritization in order to
evaluate cost effectiveness of risk reduction measures being con-
sidered. Accuracy and validity of the risk assessment are therefore
of key importance for guiding the effectiveness of disaster risk
management practice and policy.
These challenges in understanding disaster-related risk
assessment have also narrowed scientic progress on risk assess-
ment, in general. In absence of measurable indicators, risk
assessments are not monitored and evaluated for quality. There are
few linkages between the development of risk assessment metho-
dology and subsequent epidemiological validation or other mea-
sures of effectiveness.
For the past decade, most disaster health studies have extensively
investigated those risk factors associated with human vulnerability,
while very few epidemiological studies include the widely-recognized
inuences of capacity and exposure in disaster risk. Epidemiological
assessments of disaster-related health risk associated with environ-
mental disasters have also typically under-reported key risk factors
related to the environment and agent (exposure and hazard), while
focusing almost entirely on characteristics of the host (vulnerability).
Figure 1,
6,7
illustrates how disease is caused by a complex interaction
between the person (host), the disease agent (hazard), and the
environment (exposure).
There remains a need for a reproducible, well-validated,
disaster-related health risk assessment process that is suitable for
accommodating the current gaps in certainty. The purpose of this
report is to offer a practical framework and nomenclature for
assessing disaster-related health risk that is: (1) accurate; (2) based
upon historical evidence; (3) quantiable in public health terms;
and (4) inclusive of uncertainty.
7
Overview of Risk Assessment
Risk
In simplest terms, risk is the probability that an outcome will
occur. This outcome may be benecial or adverse. This relation-
ship may be represented as:
priskðÞ=ZpðoutcomeÞ:
Risk is the effect of uncertainty on outcomes.
7,8
Uncertainty is a
state or condition that involves a deciency of information and
leads to inadequate or incomplete knowledge or understanding.
Uncertainty exists whenever the knowledge or understanding of an
event, consequence, or likelihood is inadequate or incomplete.
Expressions of risk therefore include estimations of uncertainty:
priskðÞ=ZpoutcomeðÞ±uncertainty:
Impact
In general terms, risk is conceptualized as the probability of events
and the severity of outcomes (consequences) that would arise if the
events take place. The severity of consequences (usually con-
ceptualized as losses) is frequently described in terms of impact.
Correspondingly, the United Nations International Strategy for
Disaster Reduction (Geneva, Switzerland) denes impact as the
degree of severity associated with consequences.
9
Thus, the
term consequenceis not synonymous with impact.Con-
sequence is a qualitative description of the loss, while impact is a
quantitative measure of that loss.
Risk Assessment
Risk is assessed as a function of the probability that an adverse
event (referred to as a hazard) and its resultant impact will occur
during a given timeframe. This relationship is commonly descri-
bed as follows in what is commonly referred to as the risk equa-
tion:
10
pRðÞ=ZpHxIðÞ
where, R =risk; H =hazard incidence; and I =degree of impact.
The process for risk assessment is described in Figure 2 and
Table 1.
Hazard Analysis
Hazard analysis typically involves: identication of those hazards
to which the population may potentially become exposed; then
identifying the frequency of these hazards; and nally, character-
izing the adverse health effects that may result from exposure to
the hazard.
11-13
Impact Analysis
Impact analysis seeks to quantify the degree of losses (eg, disease)
that may be expected when a vulnerable population is exposed to a
hazard. Impact analysis typically involves: a determination of those
critical assets to be protected (in this case, it is the health and safety
of the population), and then an assessment of potential losses
among these assets.
11-13
For health (as a critical asset of the population), these potential
losses include disaster-related morbidity and mortality. Impact
analysis therefore includes an assessment of those risk factors
which are known to inuence disaster-related health outcomes:
namely exposures, vulnerability, and capacity.
Prehospital and Disaster Medicine
2 Assessing Disaster-Related Health Risk
Exposure Assessment
The rst step of impact analysis is to estimate the degree of hazard
exposure that the population may be expected to receive over the
time in question.
11-13
Exposures are assessed for each of the
hazards identied in the hazard analysis. Exposures are assessed in
terms of dose, which is a representation of the relative magnitude
of the hazard and its contact rate for the population over time.
When data are available, the hazard analysis includes a hazard
characterization step intended to present quantitative information
in terms of dose-response relationship (the relationship between
hazard dose and health response). The probability of exposures is
estimated through dose reconstruction and dose-response mod-
eling of many physical and biological hazards. It now appears
possible to accomplish the same for natural and human-induced
disaster hazards.
Vulnerability Assessment
Host-related factors of the target human population can inuence
susceptibility to the particular hazard, taking into account host
intrinsic and acquired traits that modify the likelihood of con-
tracting disease (susceptibility) and the likelihood of complications
(severity). Vulnerability assessments identify those (inherent and
acquired) risk and protective factors known to inuence health
outcomes, given exposure to disaster hazard has occurred.
Susceptibility is expressed as the slope of the dose-response curve.
Severity of physiological response (eg, disease) is correspondingly
expressed as a peak value on the x-axis of the dose-response curve.
Vulnerability to the same hazard may differ widely among
individuals within the same population. For example, people that
have been immunized are much less susceptible to the same degree
of exposures to viruses as compared to those who have not been
immunized. And when disease does occur, some individuals in the
population (eg, elderly or immunocompromised persons) are more
likely to suffer a more-severe course of illness, resulting in a higher
degree of impairment, disability, or even death.
Capacity Assessment
Capacity is dened as the combination of all the strengths,
attributes, and resources available in a community, society, or
organization that can be used to minimize [adverse outcomes]
following exposure to a hazard.
9
Capacity is therefore considered
as a measure of resources available to accomplish an objective.
Populations apply individual, household, community, and societal
capacity to reduce risk at every of possible stage of intervention (eg,
avoidance, reduction, transfer, and acceptance). Capacity is quite
Keim © 2018 Prehospital and Disaster Medicine
Figure 1. Causal Factors for Disease.
6,7
Prehospital and Disaster Medicine
Keim 3
complex and assessments commonly include economic, material,
behavioral, and sociopolitical resources for reducing disaster risk.
Capacity assessments are most commonly represented as an asset
inventory (ie, number of meals, amount of water, and number of
tents). However, this application recognizes only the resources of the
population. Such inventories do not take into consideration the
strengths and attributes that are also necessary in order to operate
efciently and effectively achieve the intended outcome over time.
Capacity is expressed as the rate of outputs over time (ie,
number of meals delivered per day; liters of water delivered per
person - per day; or number of tents erected per day). Thus, the
maximum capacity of the population represents a rate limiting step
for reducing disaster impact.
Capacity assessments identify those resources (eg, capabilities
with corresponding capacities) that are required to reduce the inci-
dence of disease for each of the hazards. The process is as follows:
Capability inventory - identify those capabilities that are
required to reduce disease incidence;
Expected capacity - estimate the expected capacity for each
capability in the event of disaster;
Current capacity - estimate the current capacity of the
population to reduce disease incidence; and
Gap analysis - analyze the gap between expected and current
capacity to identify mismatches.
Capacity is applied in order to treat risk at all stages of risk manage-
ment. Capacity assessment should include evaluations of capacity to be
implemented before, during, and after the disaster event.
Table 2,
14
provides examples of capabilities that can be applied
for managing health risk from environmental (eg, hydro-
meteorological, seismic, and technological), societal, and biologi-
cal disaster hazards.
Risk Characterization
Risk characterization involves the integration of the four factors
of hazard, exposure, vulnerability, and capacity to obtain a
single estimate of risk. This risk is then estimated for the adverse
health events of morbidity and mortality for disease directly
related to the hazard exposure. Risk may also be characterized for
population displacement (a signicant risk factor for disaster-
related disease).
Perhaps the best developed set of risk data is that available for
estimating hazard incidence. Expectedly, the accuracy and validity
are relatively high for predictions of commonly-occurring hazards
and, of course, less so for the more-rare hazards. Unfortunately, to
date, there are very little data available regarding exposure to health
hazards during a disaster event. It is possible to evaluate population
exposures from historical data (especially those which are collected
prospectively for the purpose of improving future risk analyses for
predictably recurrent events that are more static and reproducible
[eg, mass gatheringslike the Hajj pilgrimage]).
There are also little historical data available that are truly
predictive of population vulnerabilities as well as those corre-
sponding capacities necessary to reduce disaster-related health
risk. Vulnerability may be extrapolated to some extent by com-
paring risk factors for population vulnerability associated with
historical disaster-related outcomes. Capacities, or proxies thereof,
Keim © 2018 Prehospital and Disaster Medicine
Figure 2. Schematic Overview of Disaster Risk Management Process.
6
Prehospital and Disaster Medicine
4 Assessing Disaster-Related Health Risk
may also be compared to historical values. However, rst-order
and second-order uncertainty remain relatively high for most
public health and medical assessments of disaster-related vulner-
ability and capacity.
On the contrary, disaster-related health risk may also be fore-
casted from information directly obtained from historical data
(especially for short-term extrapolations).
For calculations involving the coming year, a simple statistical
analysis may be applied (in most cases) to estimate disaster-related
health risk according to a framework that describes the probability
of both hazards and specic health risks (Box 1).
Simple calculations of central tendency and variance readily
produce this information within an actionable framework that
relates both scale of the problem and degree of uncertainty for key
policy and decision makers. There is, of course, also the potential
to improve accuracy and perhaps validity of these annual projec-
tions by way of advanced analyses, such as logistical regression and
Monte Carlo simulation based upon historical data for both
hazards and associated health risk.
Each estimate of disaster-related health risk includes a requisite
statistical probability of a specic health outcome and the relative
degree of uncertainty regarding this conclusion. Here is an
example based upon 50 years of actual historical data of a real
country. During 2017, the mean ood-related health risk for the
population of Nation Xis predicted to occur in the form of two
declared disasters (SD =1) that are expected to cause: an annual
morbidity of 74 (SD =88); an annual mortality of 140 (SD =227);
and an expected annual displacement of 19,215 (SD =43,780)
persons. Data used for these calculations are readily available at the
national and international level.
15
Using this information alone,
conclusions may be drawn regarding the relative risk and the need
for national intervention. Considering this information (even
though the degree of uncertainty is high), it can be reasonably
concluded that the relatively small numbers of morbidity and
mortality could easily be managed according to the absorptive
capacity of the country. However, in the case of displacement,
there is the potential for over 60,000 persons displaced (as a mean,
not the worst-case scenario). This scale of displacement would
very likely require national intervention and therefore should be
considered.
Component Activities
Hazard Analysis
Hazard Identification
Hazard Probability
Identifying hazards with the potential to cause disease among the population.
Determining frequency of past hazard events.
Impact Analysis
Asset Assessment
Loss Assessment
Determining population at risk.
Identifying expected disease resulting from each hazard.
Prioritizing assets based on consequence of loss.
Capacity Assessment Identifying strengths, attributes, and resources available to counter the adverse health effects of a disaster.
Exposure Assessment Determining degree of population contact with or exposure to the hazard.
Vulnerability Assessment
Exposure
Susceptibility
Estimating degree of vulnerability of each population for each hazard.
Identifying pre-existing countermeasures and their level of effectiveness.
Countermeasure
Determination
Avoidance/Reduction
Transfer/Retention
Identifying new countermeasures which may be taken to eliminate or lessen hazards, and/or exposures and
vulnerabilities.
Cost - Benefit Analysis Identifying countermeasure costs and benefits.
Prioritizing options.
Risk Communication Preparing a range of recommendations for decision makers and/or the public.
Risk Management Plan A plan for disaster risk treatment is developed for each phase of the emergency cycle.
Implementation and
Monitoring
The risk management program is implemented and monitored per plan.
Keim © 2018 Prehospital and Disaster Medicine
Table 1. Key Components of Disaster Risk Management, as Applied to Health
6,11
Box1: Steps for a Simple Calculation of Disaster-Related Health
Risk and Uncertainty
1. Hazard Identification:
a Identify the disaster hazards that occur in target location.
2. Hazard Characterization:
a Obtain historical data for each hazard, including:
1. Hazard incidence;
2. Hazard-specific morbidity and mortality; and
3. Displacement.
b. Its helpful to include at least 30 years, a standard US
meteorological parameter.
3. Calculate the Mean and Standard Deviation for the Hazards
Annual Incidence:
a. This is described as the average annual probability of hazard
occurrence.
4. Calculate the Mean and Standard Deviation for the
Disaster-Related Health Risks Associated with this Hazard:
a. This is described as the average annual rate of disaster-
related morbidity, mortality, and displacement among the
population, plus/minus the degree of uncertainty.
Keim © 2018 Prehospital and Disaster Medicine
Prehospital and Disaster Medicine
Keim 5
Risk may also be used to prioritize interventions according to the
health impact. For example, one hypothetical risk assessment might
identify the following disaster-related health risk for a population:
Earthquake 1.0% probability of 1,000,000 deaths (SD =
5,000 deaths) =10,000 (SD =5,000) deaths;
Flood 10.0% probability of 1,000 deaths (SD =500
deaths) =100 (SD =500) deaths; or
Plane Crash 0.01% probability of 200 deaths (SD =25
deaths) =0.02 (SD =25) deaths.
Countermeasure Determination
Once hazards have been identied and prioritized according to
potential health risk, countermeasures are then identied that will
manage (or treat) the risk for each hazard.
12
Table 2 provides examples of countermeasures that may be
applied to reduce disaster-related health risk through hazard
avoidance, exposure reduction, and vulnerability reduction. These
potential countermeasures should be planned to a level of opera-
tional detail sufcient for accurate cost accounting. This is then
compared to predictions of cost-benet. When data and resources
are available, countermeasure determination should also be con-
sidered as a course of action analysis (eg, a range of options [from
doing nothingto doing everything] intended for subsequent
use by decision makers). Thus, for every countermeasure there is
an evaluation of the associated cost (eg, $USD) and expected
benet in terms of reducing disaster-related adverse health events
(eg, morbidity and mortality rates). Finally, there is the nal cost-
benet analysis that not only includes economic considerations,
but also includes value judgment involving the tolerability of risk
Stage of Prevention
Disaster Risk
Management
Capability
Capabilities for
Environmental Hazards
Capabilities for
Societal Hazards
Capabilities for
Biological Hazards
Primordial Prevention
Preventing Hazards
Risk Assessment Health surveillance
Geological and hydro-
meteorological hazard analysis
Hazard mapping
Health surveillance
Disease risk assessment
Security threat
assessment
Health surveillance
Disease risk
assessment
Hazard
Avoidance
Land use regulation
Hazard substitution
Preventive maintenance
Engineering controls
Conflict resolution
Peacekeeping
Veterinary health
Agricultural sciences
Environmental health
Public utilities and
services
Primary Prevention
Preventing Exposures
after
Hazards Occur
Risk Assessment Health surveillance
Health impact assessment
Hazard, vulnerability, and capacity
analysis
Health surveillance
Disease risk assessment
Security threat
assessment
Health surveillance
Disease risk
assessment
Hazard
Monitoring
Health surveillance
Environmental monitoring
Industrial hygiene
Health surveillance
Medical intelligence
Health surveillance
Veterinary surveillance
Vector surveillance
Exposure
Reduction
Public warning systems
Weather forecasting
Industrial hygiene
Structural mitigation
Building codes
Evacuation
Sheltering/settlement
Public warning systems
Evacuation
Sheltering/settlement
Security
Water, sanitation, and
hygiene (WASH)
Public warning systems
Isolation/Quarantine
Social distancing
Personal protective
equipment (PPE)
WASH
Secondary Prevention
Preventing Disease
after
Exposure Occurs
Risk Assessment Health surveillance
Rapid needs assessment
Exposure assessment
Damage/loss assessment
Health surveillance
Rapid needs assessment
Security threat
assessment
Health surveillance
Disease risk
assessment
Disease early warning
systems
Vulnerability
Reduction
(susceptibility)
Emergency health services
Curative health services
Risk communication
Psychosocial services
Vaccination
Emergency health
services
Curative health services
Risk communication
Psychosocial services
Emergency health
services
Curative health services
Risk communication
Psychosocial services
Tertiary Prevention
Preventing Disability/
Death after
Disease Occurs
Risk Assessment Health surveillance Health surveillance Health surveillance
Vulnerability
Reduction
(severity)
Emergency health services
Curative health services
Rehabilitative health services
Risk communication
Keim © 2018 Prehospital and Disaster Medicine
Table 2. Examples of Societal Capabilities for Prevention of Disaster-Related Mortality
14
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6 Assessing Disaster-Related Health Risk
Component Logical Framework Task List
Defining Context Given that an assessment will occur:
Define target population, P, and
disaster-related health outcome
(D
H
) to be assessed
Decide what type of disaster-related health risk is to be assessed.
Convene the risk assessment committee.
Identify the target population at risk.
Identify the number of persons included in the target population, P.
Obtain the census data (eg, demographics or SES) for the target population.
Identify health outcome and the time period for which the risk is being predicted.
Hazard Analysis Given that a target population exists,
p(P) >0:
Find probability of the hazard
occurrence p(H)
Identify all disaster hazards that could occur within the location of the target
population.
Identify the probability that each hazard will occur within the chosen period of
time (eg, 100-year flood risk).
Characterize the health hazards and resultant spectrum of human disease
associated with each disaster hazard.
Impact Analysis Given that hazards will occur,
p(H) >0:
Find probability of health impact, p(I)
When historical epidemiological data are available, calculate the probability of
disaster-related health impacts (morbidity and mortality) for each disaster
hazard along with the degree of uncertainty for each value. Then, skip to the
risk characterization component.
When historical data are unavailable, estimate health impact according to
measures or estimations of population exposure, vulnerability, and capacity as
follows:
Exposure
Assessment
Given that hazards will occur, p(H) >0,
but historical records do not:
Find probability of hazard exposure
p(E)
Estimate the proportion of the population is expected to be exposed.
Estimate the expected range for the degree of exposure received by the target
population (in terms of dose whenever possible).
Vulnerability
Assessment
Given that exposures will occur, p(E)
>0, but historical records do not:
Find probability of susceptibility,
p(V
susceptibility
)
Given susceptibility, find probability of
severity, p(V
severity
)
Estimate the expected proportion of the population that is susceptible to the disease.
Estimate the proportion of those persons susceptible to disease that would be
expected to become (temporarily) impaired.
Estimate the proportion of those persons susceptible to disease that would be
expected to become (permanently) disabled.
Estimate the proportion of those persons susceptible to disease that would be
expected to die.
Capacity
Assessment
Given that morbidity and mortality will
occur, p(morbidity >0; and
p(mortality) >0:
Find probability that predicted health
needs will exceed resources,
(p(C
predicted
)>p(C
current
)
Find disaster-related health risk,
p(D
H
)
Identify capabilities that are critical for managing the predicted number of cases
of disease associated with each hazard.
Estimate the predicted capacity of each target capability used in managing the
predicted number of cases of disease associated with each hazard.
Estimate the current capacity of each target capability for managing the
predicted number of cases of disease associated with each hazard.
Identify gaps that may exist between predicted capacity and current capacity.
Calculate excess morbidity and mortality expected to occur as a result of gaps in
health-related capacity (this is the disaster-related health risk). Proceed to risk
characterization component.
Risk
Characterization
Given that population has insufficient
capacity to reduce all disaster-related
health risks,
Characterize disaster risk and
countermeasures; perform cost
benefit analysis
Identify hazard avoidance, exposure reduction, and vulnerability reduction
countermeasures measures that may be applied to reduce risk.
Identify the expected benefits of each countermeasure.
Identify the cost of each countermeasure.
Compare the potential costs and benefits of each countermeasure.
© Prehospital and Disaster Medicine
Table 3. Logical Framework and Steps for Assessing Disaster-Related Health Risk (continued)
Prehospital and Disaster Medicine
Keim 7
according to social, cultural, political, and national security con-
cerns. This is especially important considering these judgements
include the value of health, disability, and life-years lost. For this
reason, an accurate risk assessment is important for informing a
strategy for risk communication that includes public iteration of
these value-based decisions.
Risk Communication
Once cost-effective countermeasures have been identied, these
measures must be concisely communicated to decision makers.
Messaging includes: the character of the disaster-related health
risks; the countermeasures that may be deployed to reduce risks;
the cost-benet ratio of proposed countermeasures; and nally, the
degree of uncertainty associated with the assessment.
The risk communication should also take into consideration
the target audience of the intended messaging. In most cases, the
target audience may include public ofcials and decision makers
involved in program allocations or project funding. These briengs
may therefore be more tailored to considerations of policy and
process. In other instances, the target audience may be the general
public. In this case, messaging may therefore be more directed
towards risk awareness and population protection measures.
A Logical Framework for Assessing Disaster-Related
Health Risk
Risk assessment provides a logical framework of deduction
intended to:
Predict disaster-related morbidity and mortality;
Identify countermeasures that will reduce health risk;
Compare the costs and benets of countermeasures; and
Communicate the risks and benets to a target audience.
Table 3 outlines a logical framework for risk assessment
performed for two pathways, according to availability historical
data. Both pathways result in an estimation of disaster-
related health risk in terms of the predicted number of cases.
The primary pathway depends upon historical disaster-related
health data. However, in cases where historical data may be
unavailable, health impact must be alternately estimated as a
function of exposure, vulnerability, and capacity. This secondary
pathway is therefore less likely to be predictive of outcome and
offers a lower degree of reproducibility as compared to the primary
pathway.
Limitations
Primary Pathway - When Historical Data are Available
The primary pathway of this logical framework draws from his-
torical data to calculate a reproducible representation of the evi-
dence regarding disaster-related health risk, according to
documented events. However, this model (like others currently
available) has not been validated by empirical study as truly pre-
dictive of disaster-related health risk. That is not to say that such a
study would not be feasible (as is the case for some other methods).
This modeling of predicted health-related outcomes can be readily
calculated from historical trends and then compared with real
outcomes over time. The results may then be objectively compared
for predictability.
This process represents a quantiable means for prioritizing
various disaster hazards according to potential health impact along
with at least some measure of associated uncertainty regarding this
risk. Although the degree of uncertainty is relatively high (espe-
cially for low-incidence events), it is at least objectively measured
and reported in the analysis. Albeit relatively uncertain compared
to the hard sciences, these data do represent standardized health
risk indicators associated with a measurable degree of predict-
ability and reproducibility (as compared to other methods that lack
measurable accuracy and validity).
Secondary Pathway - When Historical Data are Not Available
The secondary pathway of the framework is intended for use when
historical data are not available. This pathway offers a process that,
at present, may be reasonably considered to result in a relatively
high degree of variability for both reproducibility and predictive
value. However, the resultant information from this pathway,
though derived from non-historical estimates, is presented as
standardized health indicators, specically disease incidence. This
format does allow for representation of specic and measurable
disaster-related health risks and is suitable for aggregation of data
and cross-comparisons estimation of resource allocation and
planning purposes.
Like all such analyses, neither pathway of this framework suf-
ciently addresses the phenomenon of novel or extremely rare
events (the so-called Black Swan”–“when we dont know what we
dont know). In this case, historical data are obviously insufcient.
In addition, consensus-based decision making is poorly predictive
when the subject matter experts have limited prior experience with
the event being forecasted. There are no such models currently
available that have been validated to accurately predict disaster-
related health risk for these rare events.
Component Logical Framework Task List
Risk
Communication
Given that the potential benefits of
risk reduction countermeasures
outweigh the cost,
Communicate risks and benefits of
countermeasures to target
audience
Identify target audiences that will receive messaging regarding disaster-related
health risk and countermeasures.
Develop messages that will be delivered regarding disaster-related health risk.
Develop messages that will be delivered regarding countermeasures.
Develop messages that will be delivered regarding uncertainty of outcomes.
Develop process for monitoring and evaluating the effectiveness of
messages.
Keim © 2018 Prehospital and Disaster Medicine
Table 3 (continued). Logical Framework and Steps for Assessing Disaster-Related Health Risk
Prehospital and Disaster Medicine
8 Assessing Disaster-Related Health Risk
There are also cases when trends regarding the nature of the
hazard may be changing in a manner that is more rapid and/or
extensive as compared to the past. In this case, rapidly changing
risks (eg, extreme weather events due to climate change or stages
within a pandemic) necessitate frequent updates of when there
exists a rapidly changing hazard prole.
Conclusion
Current approaches for assessing disaster-related health risk face
signicant challenges with rst-order and second-order uncer-
tainty. Lack of a standardized nomenclature and metric for
assessing disaster-related health risk has contributed to a lack of
accuracy and reproducibility among many such assessments. An
absence of empirical data regarding disaster-related risk and pro-
tective factors, such as exposures, vulnerability, and capacity, has
resulted in a lack of validity and predictability among assessments
that rely upon these factors.
However, in many cases, accurate estimations of disaster-
related health risk may be calculated directly from historical data.
These evidence-based outcomes may be expressed in terms of rates
for morbidity and mortality. This information may then be used to
estimate the cost effectiveness of capacity that is necessary to
effectively treat the risk, thus reducing disaster-related morbidity
and mortality.
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Prehospital and Disaster Medicine
Keim 9
... It is caused when hosts are exposed to an environment containing agents that are hazardous to health. It is therefore possible to study the causal factors involving the agent (i.e., hazard), host (i.e., vulnerability), and environment (e.g., exposure), including both risk and protective factors (Keim 2017(Keim , 2018a(Keim , 2018b. ...
Presentation
Guest Lecturer, Disaster Medicine 201: Post-Earthquake Medical Challenges in the New Madrid Seismic Zone Title: The public health impact of climate change and Concept of operations for mass casualty management Festus, MO March 18-19, 2010
Article
The main purpose of the research is to improve the efficiency of management decisions in the field of environmental protection through using the methods for assessing the public health risk at the current level of air pollution. Methodology. The article presents a hierarchical methodological approach for determination of the level of air pollution hazard at the state, regional and local levels. The state of atmospheric air is greatly affected by emergencies associated with accidents at chemically hazardous facilities, which result in burst releases of hazardous chemicals into the environment. When determining the environmental risk of deterioration in the state of atmospheric air, the chemical hazard indicator was taken into account. Results. On the territory of the East of Ukraine there is the largest number of potentially dangerous enterprises. A new methodology of determination of the hazard level of air pollution is presented at the existing trends of anthropogenic load and the possible occurrence of technogenic emergencies. Assessment of public health risk due to air pollution in the Mariupol city showed an extremely high level of danger. The determination of the risk as a macroecological indicator according to the new method shows a high level of hazard of air pollution in the industrial developed regions of Ukraine. The shortcomings of the methodical approach of the United States Environmental Protection Agency (EPA US), widely used in many countries of the world, are shown. An analysis of methodological approaches to assessing the public health risk has shown the promise of using the methodology for assessing potential risk in determining the level of environmental hazard of industrial enterprises. The assessment of the public health risk in the current quality state of air is given by two different methods for the regions of Ukraine with a high level of ecological and chemical hazard. The improvement of the methodology for assessing the risk to public health due to air pollution is proposed, which is presented as a scientific novelty. Currently when Ukraine has been affected by hostilities and the economic crisis, the issue of priority funding for environmental protection is very important. The implementation of the proposed methodological approach will make it possible to scientifically determine regions with an increased level of hazard to public health and minimize financial resources for improving the air quality, which has actual practical significance.
Technical Report
Full-text available
In 2007, Dr Mark Keim, then Associate Director of the NCEH/ATSDR Office for Terrorism Preparedness and Emergency Response, requested GRASP to produce a white paper that catalogs readily available population and hazard identification data sources that can be used within a GIS to identify populations vulnerable to hazards. GIS tools and methods for population vulnerability analysis are also discussed.
Article
Full-text available
Global warming could increase the number and severity of extreme weather events. These events are often known to result in public health disasters, but we can lessen the effects of these disasters. By addressing the factors that cause changes in climate, we can mitigate the effects of climate change. By addressing the factors that make society vulnerable to the effects of climate, we can adapt to climate change. To adapt to climate change, a comprehensive approach to disaster risk reduction has been proposed. By reducing human vulnerability to disasters, we can lessen—and at times even prevent—their impact. Human vulnerability is a complex phenomenon that comprises social, economic, health, and cultural factors. Because public health is uniquely placed at the community level, it has the opportunity to lessen human vulnerability to climate-related disasters. At the national and international level, a supportive policy environment can enable local adaptation to disaster events. The purpose of this article is to introduce the basic concept of disaster risk reduction so that it can be applied to preventing and mitigating the negative effects of climate change and to examine the role of community-focused public health as a means for lessening human vulnerability and, as a result, the overall risk of climate-related disasters. ( Disaster Med Public Health Preparedness . 2011;5:140–148)
Presentation
Guest Lecturer, New York University First Annual Symposium of Urban Disaster Medicine Title: Intentional Chemical Disasters New York, NY, USA September 20, 2003
Article
Objective. County-level socioeconomic and demographic data were used to construct an index of social vulnerability to environmental hazards, called the Social Vulnerability Index (SoVI) for the United States based on 1990 data. Methods. Using a factor analytic approach, 42 variables were reduced to 11 independent factors that accounted for about 76 percent of the variance. These factors were placed in an additive model to compute a summary score-the Social Vulnerability Index. Results. There are some distinct spatial patterns in the SoVI, with the most vulnerable counties clustered in metropolitan counties in the east, south Texas, and the Mississippi Delta region. Conclusion. Those factors that contribute to the overall score often are different for each county, underscoring the interactive nature of social vulnerability-some components increase vulnerability; others moderate the effects.
Topic collection: hazard vulnerability/risk assessment
  • H A Tracie
Tracie HA. Topic collection: hazard vulnerability/risk assessment. 2017. https:// asprtracie.hhs.gov/technical-resources/3/Hazard-Vulnerability-Risk-Assessment/0. Accessed August 30, 2017.
How do people die in disasters and what can be done?
  • M Keim
  • J Abrahams
  • J Castilla-Echenique
Keim M, Abrahams J, Castilla-Echenique J. How do people die in disasters and what can be done? http://disasterdoc.org/how-do-people-die-in-disasters/. Accessed August 30, 2017.
The social vulnerability index
GRASP. The social vulnerability index. 2017. https://svi.cdc.gov/. Accessed August 30, 2017.
Risk management basic concepts in general principles
  • F Wharton
Wharton F. Risk management basic concepts in general principles. In: Ansell J, Wharton F, (eds). Risk Analysis Assessment and Management. Chichester, UK: Wiley & Sons; 1992: 100.
Disaster Risk Management for Health
  • M Keim
Keim M. Disaster Risk Management for Health. In: David S, (ed). Textbook of Emergency Medicine. Chicago, Illinois USA: Wolters Kluwer Health (Lippincott); 2010: 1309-1318.