Epidemiology
From Wikipedia, the free encyclopedia.
Epidemiology is the study of the distribution and
determinants of health-related states or events in specified populations, and
the application of this study to control of health problems (Last 2001).
Epidemiology is the scientific study of factors affecting the health and
illness of individuals and populations, and, in this capacity, it serves as the
foundation and logic of interventions made in the interest of the public’s
health.
The acting epidemiologist works on issues from the practical, such as
outbreak investigation, environmental exposure, and health promotion, to the
theoretical, including the development of statistical, mathematical,
philosophical, and biological theory. To this end, epidemiologists employ a
range of study designs from the observational to experimental with the purpose
of revealing the unbiased relationships between exposures such as nutrition,
HIV, stress, or chemicals to outcomes such as disease, wellness, and health
indicators.
Epidemiological studies are generally categorized as descriptive,
analytic (aiming to examine associations, commonly hypothesized causal
relationships), and experimental (a term often equated with clinical or
community trials of treatments and other interventions).
Epidemiologists work in a variety of settings. Some epidemiologists work
"in the field", i.e., in the community, commonly in a public health
service, and are at the forefront of investigating and combating disease
outbreaks.
Epidemiology
as causal inference
Although epidemiology is sometimes viewed as a collection of statistical
tools used to elucidate the associations of exposures to health outcomes, a
deeper understanding of this science is that of discovering causal
relationships. This conceptualization of epidemiology is difficult to grasp
because our internal notions of causation are often poorly developed,
frequently being predicated on the notion of a one-to-one relationship. For
example, almost everyone would agree that gravity causes a dropped ball to fall
towards the ground, but would most agree that drinking one glass of milk a day
will cause weight loss? Even very heavy smokers know that their vice causes
lung cancer, but only 10% of life-long smokers will get lung cancer. How can
this be?
The answer is complex and delves into the
philosophical notions of causality, induction, deduction, logic and other dense
topics. It is nearly impossible to say with perfect accuracy how even the most
simple physical systems will behave, much less the complex field of
epidemiology that draws on biology, sociology, mathematics, statistics,
anthropology, psychology, and policy. However, for the epidemiologist the key
is in the term inference. As epidemiologists, we use gathered data and a broad
range of bio-medical and psycho-social theories in an iterative way to generate
or expand theory, to test hypotheses, and to make educated, informed assertions
about which relationships are causal and exactly how they are causal.
Epidemiology
as advocacy
An alternative aspect of an epidemiologist’s duty is
to advocacy for the health of populations, bearing in mind the outpost
perspective they have over factors that affect a whole population. In this
capacity the epidemiologist is not limited by the strict requirements for
scientific accuracy. This of course does not mean that the epidemiologist can
advocate for whatever position they please independent of the data, but
presentation of the data can take more artistic modes to engender behavior or
perspective change. For example, consider these two alternative admonishments
against smoking:
1. smoking has been
consistently linked to health problems such as lung cancer and coronary heart
disease in several large prospective studies, this link has been deemed causal
by a complex process of induction, consensus, and modeling.
2. Smoking will kill you. Although statement one is
more accurate, statement two has an air of finality and explicit causation that
may help to reduce the rate of smoking, albeit scientific and philosophically
questionable.
The best epidemiologist as advocate will consider
the broader intellectual landscape beyond the epidemiology and public health literature
to render judgment on a course of action for a population,
in this manner they are employing a different analytical framework than the
Cartesian framework that is more common in scientific epidemiology. However, it
is rare for one person to wield the skills and embody the features required to
be a leader in both the scientific and advocacy aspects of epidemiology.
Measures
Dr. John Snow is famous for the suppression of an 1854 outbreak of
cholera in
Other pioneers include Danish physician P.A.
Schleisner, who in 1849 related his work on the prevention of the epidemic of
tetanus neonatorum on the
In the early 20th century, mathematical methods were
introduced into epidemiology by Ronald Ross, Anderson Gray McKendrick and
others. Another breakthrough was the
1956 publication of the results of a British doctor's study, which lent
statistical support to the suspicion that tobacco smoking was linked to lung
cancer.
References
Analyzing Multiple Risk Factors
Listed below are some of the
initial steps that take place in an outbreak investigation. This section
will provide you with a basis of information to complete this module.
Background Information
Recently, a national political action committee (PAC) held a fundraising event
at a Hotel & Convention Center in
The candidate would be selected
by a popular vote that was scheduled to occur at the completion of the annual
meeting, which took place during August 28--31. Upon arrival at the
meeting, members of the PAC attended a banquet to recognize the accomplishments
of the group during the previous calendar year.
Within 24 hours of the banquet, a
number of diners had become ill with diarrhea and at least one of the following
symptoms:
-
Headache
-
Fever
-
Abdominal
pain
-
Nausea
-
Vomiting
At this
point, the local public health department has been notified and is onsite to
conduct an investigation.
Identifying an Outbreak
Often, health departments
are alerted of a potential outbreak by a health-care provider or the general
public. It is your responsibility to identify whether the event is truly
an outbreak or a series of unrelated cases.
Establishing a Case Definition
A case definition is a
"set of standard criteria for deciding whether a person has a particular
disease or health-related condition, by specifying clinical criteria and
limitations on time, place, and person" (1). In the beginning
of an investigation, the case definition can be fairly general, but as
information is gathered, the epidemiologist may use a more specific
description.
Initial Case Definition
An illness with diarrhea and at least one of the following symptoms: headache,
fever, abdominal pain, nausea, and/or vomiting. Onset of illness or
symptoms occurred during August 28--31.
Identification of Cases
Often, the initial cases
identified in an investigation represent only a fraction of the affected
population. Therefore, it is important to detect and identify other cases
through interviews, questionnaires, surveys of health care facilities, newspaper
articles, and other means.
During the next
part of the outbreak investigation, the team obtained an occupancy list of all
of the guests who were registered at the hotel.
Using an adapted version of the
foodborne outbreak investigation questionnaire developed by CDC, which
contained questions pertaining to demographics, clinical information, exposure
information, and a 72-hour meal history, the team divided the list and began to
collect data in an effort to identify affected cases and systematically organize
key information.
The
team established that 105 of the 435 hotel guests had become acutely ill and
exhibited many of the symptoms listed in the initial case definition. All
of these persons were members of the
Formulating Hypotheses
The next step in an investigation is to develop an initial hypothesis, based
upon the information collected during early interviews and other information provided by health-care facilities or medical
institutions that treated the patients.
Initial Hypothesis
Onset of diarrheal illness of an unknown origin occurred during August
28--31. The potential exposure to the unknown agent could have occurred
at the PAC banquet at Hotel A in
Evaluating
the Hypothesis
In order to identify the
source of the epidemic, investigators must evaluate the relationships between
exposures and the disease in question. The following information will be
helpful in evaluating the hypothesis presented on the following pages.
Additional
Information
A descriptive analysis of
the information gathered from the interviews and questionnaires identified the
following characteristics of the distribution of the disease in question.
This information suggests that attendance at the banquet was the
common exposure, and the reported symptoms sound like an outbreak of
gastroenteritis, which is commonly caused by food contamination.
Next, we will discuss
methods to organize the data in an effort to begin to make epidemiologic
associations.
Potential
Exposures
The
team was able to determine from the interviews that the potential exposures in
this outbreak include all the items served at the banquet:
-
-
Gravy
-
Ham
-
Mashed
potatoes
-
Green
beans
-
Chocolate
sorbet
-
Strawberry
sorbet
We
need to discover, each of the potential exposures, which is associated with
becoming ill.
Risk Factors
All of
the potential exposures cited in the scenario so far could be classified as risk
factors, which can be defined as "an aspect of personal behavior,
lifestyle, or environmental exposure...which, on the basis of epidemiologic
evidence, is known to be associated with a health-related condition considered
important to prevent".(1)
Since we are trying to
determine what factors are associated with the illness, we must analyze the
data in order to measure the frequencies with which a potential exposure can be
associated with the illness. Measures of association may be expressed in
several ways.
Attack
Rates
One of
the most commonly used measures expresses how many diseases are
a consequence of a certain factor. It can be expressed as an
attack rate, which measures the proportion of people in a well-defined
population that develop an illness of interest during a limited period of time.
These
rates can be calculated by dividing the number of new cases among the
population during the limited time period (X) by the population at risk
at the beginning of the period (Y). This number is then multiplied
by (100) to obtain a percentage. The formula can be expressed as:
As you
can see, attack rates measure the probability or risk for becoming a
case. So the greater the difference between attack rates for those
exposed to a particular risk factor and those not exposed, the higher the
probability that the risk factor caused the outbreak. Let's
look at our previous example to calculate the attack rate for the entire
population who attended the PAC banquet: X = the number of ill persons who
attended the banquet = 105 Risk Ratio Before
we can make any conclusions, we must also calculate the attack rates for the unexposed
population (i.e., the population that did not eat the menu
item). In the table below, we have provided you with the attack rate of
both the exposed and unexposed population so that we will be able to calculate
the risk ratio. The risk ratio compares the amount
of disease risk in the exposed population to the amount of risk in the
unexposed population. The formula can be expressed as: Risk
ratios can be evaluated by using the following criteria: -
RR
= 1.0 indicates
identical risk in both groups -
RR
> 1.0 indicates an
increased risk for the exposed group compared to the unexposed group -
RR
< 1.0 indicates a
decreased risk for the exposed group compared to the unexposed group Selection
of an appropriate reference or comparison group is critical to determining
whether an association exists between the exposure and illness.
Typically, the reference group is the population of individuals that has had no
exposure to the risk factor being analyzed. Ideally, the exposed and
unexposed populations should be similar, with the exception of the
exposure. Thus, if no direct association exists between the exposure and
the illness, the attack rates will be relatively similar. Unfortunately, the analysis of food-specific attack rates did not
clearly point to any one of the menu items as the source of the outbreak. However, one of the
epidemiologists pointed out that eight persons arrived late to the banquet and
were able to eat only dessert. All of these persons became ill. Of these eight dessert-only
diners: In addition, the outbreak
investigation team realized through their analysis of the data that ten persons
who ate the main course of the meal did not eat dessert. Of these ten
non-dessert diners, only two became ill. Analyses of Multiple
Risk Factors "It is important to note
that when several risk factors are being considered simultaneously, the
non-exposed group should be defined as those with none of the risk factors
under evaluation".(2) In this case, the reference group is
the population of individuals that were not exposed to (did not eat) the risk
factors being analyzed. We have established the group
that ate no dessert as the "risk-free" reference group, as they have
many of the same characteristics of the exposed population but did not eat any
of the dessert items. Previously, when the risk ratios
were calculated for the two dessert items, they were 1.32 for chocolate
sorbet and 1.07 for strawberry sorbet. There is a difference between
these figures and those calculated above (2.25 for chocolate sorbet and 2.00
for strawberry sorbet). There are several reasons for this
discrepancy listed below. -
Two
high-risk populations were compared because the comparison (unexposed) group
included all those who ate the other implicated food item (minus those who ate
both items). -
The
resulting attack rate for the comparison (unexposed) group was relatively
similar to the attack rate for the exposed population. -
Therefore,
the risk ratios were relatively low and did not appear to be statistically
significant.
Y = the total number of persons who attended the banquet = 235
Selecting a Reference Group
Knowing when to refocus and
reanalyze like this is not easy; it is something that investigators generally
learn from judgment and experience. It is also essential to stay open
and alert to clues. A key clue was that among a small number of people
who ate nothing but dessert, all became ill, and among a small number who ate
no dessert, few became ill.
Further Investigation
After a thorough analysis of the
data, the investigation team hypothesized that the primary contributing factors
to the illness were associated with eating chocolate sorbet or strawberry
sorbet.
Early in the investigation, stool
specimens had been taken from several persons. In addition, the team also
took stool samples from all of the kitchen staff on duty during the preparation
of the food for the banquet. All of the samples were sent to the local
health department lab to be cultured for enteric pathogens.
Revising the Hypothesis
Once you have characterized the outbreak by time,
place, and person and analyzed the data to determine risk factors associated
with the disease, it is helpful to revisit the initial hypothesis and to
determine if any changes need to be made on the basis of the information
gathered so far. Much of this information can be derived from descriptive
epidemiology and the analyses of the individual risk factors.
For instance, we are able to
deduce that the vehicles for transmission of the illness were chocolate sorbet
and strawberry sorbet. Unfortunately, at this point the causative agent (such
as a microorganism, chemical substance, or form of radiation, whose presence,
excessive presence, or relative absence is essential for the occurrence of a
disease) is still unknown, and additional data will therefore need to be
gathered after the revised hypothesis is developed.
Our revised hypothesis could read
"The illness was caused by consumption of either chocolate sorbet
and/or strawberry sorbet consumed at the Political Action Committee Banquet at
6 p.m. on August 28.
When the results were returned
from the lab, the results indicated that:
-
No
kitchen staff tested positive for any enteric pathogens,
-
Stool
cultures from the early onset cases tested positive for Salmonella Typhimurium,
-
Cultures
from the leftover chocolate sorbet and strawberry sorbet yielded the identical
strain of Salmonella to the persons tested at the banquet.
Based upon this new information,
the investigation team revised their case definition to read:
-
An
illness with diarrhea (multiple loose bowel movements within a 24-hour period)
and at least one of the following symptoms: headache, fever, abdominal pain,
nausea, and/or vomiting
OR
-
A
positive stool culture for Salmonella Typhimurium
AND
-
Onset
of illness or symptoms occurred during August 28--31 and the patient attended
the PAC banquet.
In addition, local sanitarians
also conducted an environmental analysis of the kitchen facility and found no
indication of Salmonella Typhimurium on any of the equipment or utensils
that were used in the storage, preparation, and service of the
meal. In addition, they also found that the kitchen staff practiced
good hygiene and safe food-handling practices.
Understanding the
Outbreak
Many outbreak investigations are
not straightforward, and this one is no exception. Another aspect of
evaluating a hypothesis is to review reference material on the disease or
illness to determine whether the situation is similar to other reported
incidents. Often, the Emerging Infectious Diseases (EID) journal is a
valuable resource for finding incidents, trends, and specific disease
information. (EID is available at: //www.cdc.gov/ncidod/EID/.
Some of the areas that will help
with the investigation are:
-
Typical
signs and symptoms
-
Modes
of transmission
-
Exposures
In the example of the PAC
Banquet, the majority of ill persons interviewed met the established symptoms
of Salmonella Typhimurium, such as:
-
Diarrhea,
fever, and abdominal cramps
-
Incubation
period of 6 -- 72 hours after infection
-
Illness
usually lasts 4 -- 7 days
-
Transmitted
through contaminated food, water, or contact with infected animals
However, the fact that Salmonella
Typhimurium is not typically found in the ingredients used in chocolate sorbet
and strawberry sorbet led the investigation team to consider the possibility of
deliberate tampering.
When the investigators first
suspected intentional food tampering, they contacted local law enforcement
officials, who in turn notified the Federal Bureau of Investigation
(FBI).
Information obtained in the
ensuing investigation revealed that a supporter of one of the candidates owned
the company that supplied desserts to many of the food service facilities in
the area. This person later admitted to trying to sabotage the election
by inoculating Salmonella Typhimurium into the desserts in an attempt to
alter the results of the popular vote for funding. The saboteur and
colleagues skipped the banquet and had planned to show up for the vote while
others were ill.
If you recall, there were two
persons reported that they did not eat the dessert. As it turns out, when
asked again, they indicated that they forgot to mention taking a "few bites"
from their spouses' desserts.
Also, four hotel employees who
were not employed in the kitchen, were identified as
having Salmonella Typhimurium. These employees became ill after
they ate desserts that had been left over from the banquet.
In the end, all of the cases were
accounted for and associated with either chocolate sorbet or strawberry sorbet.
Summary
Many outbreak investigations are
not straightforward, and therefore it is important to look for clues that will
help you identify what factors are associated with the illness in
question. To accomplish this, you should select an appropriate reference
group and analyze the data for measures of association. The following is
a brief description of the steps involved in this process.
Selecting a Reference Group
Selection of an appropriate reference or comparison group is critical to
determining whether an association exists between the exposure and
illness. Typically, the reference group is the population of individuals
that has had no exposure to the risk factor being analyzed. Ideally, the
exposed and unexposed populations should be similar, with the exception of the
exposure. Thus, if no direct association exists between the exposure and
the illness, the attack rates will be relatively similar.
Calculating Rates and Ratios
To determine what factors are associated
with the illness, we must analyze the data to measure the frequencies with
which a potential exposure can be associated with the illness. There are
several ways to express measures of association in cohort studies.
-
Attack
rates are calculated by
dividing the number of new cases among the population during the limited time
period (X) by the population at risk at the beginning of the period (Y).
This number is then multiplied by (100) to express in a
percentage. The formula can be expressed as:
-
Risk
ratios compare the amount
of risk associated with an event such as a disease or death in the exposed
population to the amount of risk in the unexposed population. As a
result, they are calculated by dividing the attack rate in the exposed
population by the attack rate in the unexposed population. The formula
can be expressed as:
Analyzing Multiple Risk
Factors
When several risk factors are being considered
simultaneously, it is often necessary to establish an experimental control,
where there is an absence of exposure to all of the risk factors being
analyzed. By establishing an experimental control, a uniform denominator
is created and the resulting risk ratios can be compared. The following
can assist with comparison of risk ratios.
-
RR
= 1.0 indicates
identical risk in both groups
-
RR
> 1.0 indicates an
increased risk for the exposed group compared to the unexposed group
-
RR
< 1.0 indicates a
decreased risk for the exposed group compared to the unexposed group
Identifying the correct
association will the illness does not always occur on the first attempt and
knowing when to refocus and reanalyze often requires experience and judgment
and might require advanced analysis. Often, investigations are an iterative
process in which a hypothesis is established, tested, and revised several times
before association(s) can be established. Overall, it is also essential
to stay open and be alert to clues
Copyright ©2000-2019 Geigle Safety Group, Inc. All rights reserved. Federal copyright prohibits unauthorized reproduction by any means without permission. Disclaimer: This material is for training purposes only to inform the reader of occupational safety and health best practices and general compliance requirement and is not a substitute for provisions of the OSH Act of 1970 or any governmental regulatory agency. CertiSafety is a division of Geigle Safety Group, Inc., and is not connected or affiliated with the U.S. Department of Labor (DOL), or the Occupational Safety and Health Administration (OSHA).
