Introduction to Epidemiology
Introduction
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Edward Jenner (1749-1823) developed a vaccine
against small pox using cow pox, 160 years before
virus was identified
John Snow (1813-1858) described an association
between dirty water and cholera, 44 years before
Vibrio cholera was identified
Hill and Doll in a case control study demonstrated
that smoking and lung carcinoma are related
Framingham study ( 50 years follow up)showed
people a certain group of people were at risk
Intro.
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Fundamentals of epidemiology
Sources of data
Causation
Review of terms
Classically speaking
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Epi = upon
Demos = people
Ology = science
Epidemiology = the science which deals
with what falls upon people…..
Bridge between biomedical, social and
behavioral sciences
Definition
Study of the occurrence and distribution of
health-related diseases or events in
specified populations, including the study of
the determinants influencing such states,
and the application of this knowledge to
control the health problem
(Porta M, Last J, Greenland S. A Dictionary of Epidemiology, 2008)
Who is an epidemiologist ?
A professional who strives to study and
control the factors that influence the
occurrence of disease or health-related
conditions and events in specified populations
and societies, has an experience in population
thinking and epidemiologic methods, and is
knowledgeable about public health and causal
inference in health
(Porta M, Last J, Greenland S. A Dictionary of Epidemiology, 2008)
Requirements in Epi
• Public health: because of the emphasis on disease prevention
•Clinical medicine: because of the emphasis on disease
classification and diagnosis (numerators)
• Pathophysiology: because of the need to understand basic
biological mechanisms in disease (natural history)
• Biostatistics: because of the need to quantify disease frequency
and its relationships to antecedents (denominators, testing
hypotheses)
• Social sciences: because of the need to understand the social
context in which disease occurs and presents (social determinants
of health phenomena)
Purposes of Epi
1.
2.
3.
4.
5.
To investigate nature / extent of healthrelated phenomena in the community /
identify priorities
To study natural history and prognosis
of health-related problems
To identify causes and risk factors
To recommend / assist in application of
/ evaluate best interventions
(preventive and therapeutic measures)
To provide foundation for public policy
Traditional Epidemiology
Triangle
Environment
Time
Host
Agent
Modern Epidemiology Triangle
Causative Factors
Time
Groups
of Populations
Physiological Factors,
Environment,
Behavior, Culture
Ecological Elements
Disease Stages in Individuals
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Clinical disease: characterized by signs
and symptoms
Nonclinical disease:
 Preclinical: not yet clinically apparent
 Subclinical: not clinically apparent and
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stays that way
Chronic: persists for years (can also refer
to clinical disease
Disease Stages in Populations
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Endemic: the level of a disease that is
“normal” for a population
Epidemic: when the level of disease
occurs in excess of the normal level for
that population
Pandemic: an epidemic that occurs
across many populations or even the
entire world
Modes of Transmission
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Direct: person to person
Indirect: needs an intermediate item
(water, food, flies, etc.)
Disease Transmission by
People
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Carriers: exposed and harbors disease
 Active: can transmit even though they are
better
 Convalescent: transmit while convalescing
 Healthy or passive: can transmit even
though they never get sick
 Incubatory: transmit before developing
symptoms
Case Concepts
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Case: person with the disease/problem
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Primary case: first case in a population
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Index case: first identified case
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Suspect case: all signs of disease but no
diagnosis
Case Concepts
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Case definition: standard criteria for
case
Case severity: length of hospital stay,
disability, fatality, etc
Levels of Prevention
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Primary: prevent acquisition of disease
Secondary: screening for early
detection of disease
Tertiary: prevention of disability from
disease
Epidemiologic ( scientific ) Approach
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1. Identify a PROBLEM :
clinical suspicion ; case series ; review of medical literature
2. Formulate a HYPOTHESIS ( asking the right question )
;
good hypotheses are: Specific, Measurable, and Plausible
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3. TEST that HYPOTHESIS ( assumptions vs. type of data
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4. always Question the VALIDITY of the result(s) :
Chance ; Bias ; and Causality
Epidemiologic Study: threats to Validity
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Chance : role of random error in outcome
measure(s)
( p - value ; power of the study and the confidence
interval )
--- largely determined by sample size
Bias : role of systematic error in outcome
measure(s)
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Selection bias - subjects not representative
Information bias - error(s) in subject data /
classification
Confounding - 3rd variable (causal) assoc. w/ both X
and Y
What is a hypothesis?
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An educated guess
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an unproven idea
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based on observation or reasoning, that
can be proven or disproven through
investigation.
What goes into a hypothesis?
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Characteristics of the disease
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The illness
Established modes of transmission
Distribution
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In time
By place
By person
Hypothesis
(1st Step in the Epidemiologic Approach)
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Developed prior to a study to state
research purpose
Is established to either accept or
refute
Ideal Hypothesis
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Should include
 The population
 The cause being considered
 Expected effect
 Dose-response relationship
 Time response relationship
Sources of Data
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Vital records for epidemiologic study
 Birth certificates
 Death certificates
 Marriage licenses
Determining Cause
Relationship
Association
Real or spurious??
Cause
Definition of Cause
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Cause: an antecedent event, condition,
or characteristic that was necessary for
the occurrence of the disease at the
moment it occurred given that other
conditions are fixed
Types of Cause
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Direct cause: factor causes outcome
without any intermediate factor
(without intermediate steps)
Indirect cause: factor causes disease
but with an intermediate factor (with
intermediate step or steps)
Evolution of Causal Theory
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1880 - Koch’s Postulates
1965 - A. B. Hill’s Criteria for
Causation (public health
perspective)
Current - Epidemiologic specific
guidelines for cause
Koch’s Postulates
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Causative organism is always present
with disease
Causative organism is not found in
any other disease
An organism isolated from a case is
able to produce disease
Isolated organism can be grown in the
laboratory
Hill’s Criteria of Causation
1)
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Consistency with other investigations
Strength of association
Specificity
Dose response relationship
Temporal relationship
Biologic plausibility
Coherence
Experiment
Epidemiologic-Specific
Guidelines for Cause
1)
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Cause should be distributed the same as
outcome
Incidence should be higher in exposed
Exposure should be higher in deceased
Temporal sequence
Dose response relationship
Cause and effect should be associated even
with different study designs
Epidemiologic-specific
Guidelines
7)
8)
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high magnitude of association
Control methods should work
Individual control methods should
result in a change in whole population
Consistency with animal studies
Biologic plausibility
Causal Relationships
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Necessary and sufficient
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without the factor disease will not develop
with the factor disease always develops
(HIV/AIDS)
Necessary but not sufficient
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factor present, but low dose
part of a group of multiple factors
(carcinogens/cancers)
Causal Relationships
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Sufficient but not necessary
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Neither sufficient nor necessary
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factor can act alone to cause disease, but other
factors can cause the same disease
(radiation/leukemia)
complex model
(hypertension)
Causal complement
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set of conditions necessary and sufficient for a
factor to produce disease, rapid, synergistic
(smoking & asbestos/lung cancer)
Broad Types of Epidemiology
DESCRIPTIVE EPI
Examining the distribution of a
disease in a population, and
observing the basic features of its
distribution in terms of time,
place, and person. We try to
formulate hypothesis, look into
associations ?
Typical study design:
community health survey
(synonyms: cross-sectional
study, descriptive study)
ANALYTIC EPI
Testing a specific hypothesis
about the relationship of a
disease to a specific cause, by
conducting an epidemiologic
study that relates the
exposure of interest to the
outcome of interest (? Causeeffect relationship)
Typical study designs: cohort,
case-control, experimental
design
Descriptive Epidemiology Is A Necessary
Antecedent of Analytic Epidemiology
To undertake an analytic
epidemiologic study you must
first:
 Know where to look
 Know what to control for
 Be able to formulate / test
hypotheses compatible with apriori lab / field evidence
Basic Triad of Descriptive
Epidemiology
THE THREE ESSENTIAL CHARACTERISTICS
OF DISEASE WE LOOK FOR IN DESCRIPTIVE
EPIDEMIOLOGY ARE:
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PERSON
PLACE
TIME
Personal Characteristics (whom)
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Age
Gender
Socio-economic status (education,
occupation, income)
Marital status
Ethnicity/race/genetic profile
Behavior / habits
Place (where ?)
Geographically restricted or
widespread (outbreak, epidemic,
pandemic)? Off-shore (tsunami…)
 Climate effects (temperature,
humidity, combined effects..)
 Urban / sub-urban-squatter / rural
 Relation to environmental exposure
(water, food supply, etc)
 Multiple clusters or one?
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Time (when ?)
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Changing or stable?
Clustered (epidemic) or evenly
distributed (endemic)?
Time-trends: Point source,
propagated, seasonal, secular,
combinations
What designs do
epidemiologists use ?
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Qualitative designs
Quantitative designs
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Observational
Experimental
Building evidence
What measures do
epidemiologists use ?
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Frequency measures
Effect measures
Impact fractions
Measuring Disease Frequency
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Classifying and
categorizing disease
Deciding what
constitutes a case of
disease in a study
Finding a source for
ascertaining the cases
Defining the
population at risk of
disease
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Defining the period
of time of risk of
disease
Obtaining
permission to study
people
Making
measurements of
disease frequency
Relating cases to
population and
time at risk
Agents
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Biological (micro-organisms)
Physical (temperature, radiation,
trauma, others)
Chemical (acids, alkalis, poisons,
tobacco, others)
Environmental (nutrients in diet,
allergens, others)
Psychological experiences
Host Factors
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Genetic endowment
Immunologic status
Personal characteristics
Personal behavior
Definitive versus intermediate
(in vector-borne diseases)
Environment
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Living conditions (housing, crowding,
water supply, refuse, sewage, etc)
Atmosphere / climate
Modes of communication:
phenomena in the environment that
bring host and agent together, such
as: vector, vehicle, reservoir, etc)
Epidemiology as a problem solving
discipline: Integrating principles
The first integrating principle is that
epidemiology is an information science.
The second integrating principle is that
epidemiology operates within an
environment of complex systems.
Third integrating principle is that
epidemiology is not just a scientific
discipline but a professional practice
area.
(I)
Epidemiology is an
information science
Epidemiology is an information science:
Data generated by epidemiologists is to be
used for decision making.
Epidemiology is purposive: methods and
knowledge are to be used for the ultimate
purpose of prevention of disease, disability
and death
Epidemiology is under public scrutiny.
Information affects decisions at the public
policy level, at the level of individuals, and by
health professionals. A social responsibility.
INFORMATION
GENERATION
 DECISION  ACTION
PROCESS
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EPIDEMIOLOGIC  PROCESS OF  INTERVENTION
METHODS
INFERENCES
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Prevalence
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How many cases of disease already
exist in a population at a specific time
Proportion
Static measure; time is frozen
Why would you want to know about
prevalence of a disease?
Calculation of Prevalence
# of current cases ( old and new)
Size of population at risk at that time
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Prevalence is a proportion and can
never exceed 100%
Expressing Prevalence
Prevalence of diabetes in Clinic X:
116/184 =0.63
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63%
630 per 1000
6300 per 10,000
Incidence
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The rate at which new cases of disease
develop in a population over time
e.g. how many new cases of diabetes
were diagnosed in one year at Clinic X?
When would you want to know
incidence versus prevalence?
Incidence Calculation
# of new cases or number of events
population at risk during the same period
(for a long period use the midpoint of the population level)
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Incidence is a measure of risk
All persons should be disease-free at the
beginning of the interval*
*in practice they aren’t always excluded
Calculating Incidence
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Among 60 people attending a 12 month residential
detoxification program, 50 tested HIV negative at
the start of the program in Jan 1998. At the end of
the program in Dec 1998, 3 of the 50 tested
positive for HIV.
What is the cumulative incidence of HIV infection?
3/50 = 6% per year
It is important to pay attention to the time
period. A cumulative incidence of 6% per month
is a much greater rate than 6% per year.
Calculating Incidence
3/50 = 6% per year
It is important to pay attention to the
time period. A cumulative incidence of
6% per month is a much greater rate
than 6% per year