Download Epidemiology

Introduction to Epidemiology and
the Epidemiology Modules
Today
What is Epidemiology?
Measures that are important in all of epidemiology
Why I never believe anything I read in the newspaper
The three modules and how they fit into the big
picture
What is Epidemiology?
Greek
(English)
epi
(among)
demos
(people)
logy
(study)
What is Epidemiology?
The study of the distribution and determinants
of health and disease related states in
populations,
and the application of this study to control
health problems.
(John M. Last)
What is Epidemiology?
The study of the distribution and determinants
of health and disease related states in
populations,
and the application of this study to control
health problems.
“the product of [epidemiology] is research and information
and not public health action and implementation”.
(Atwood et al. 1997)
“epidemiology’s full value is achieved only when its
contributions are placed in the context of public health action,
resulting in a healthier populace.” (Koplan et al. 1999)
“Epidemiology . . .
is a Greek word that means to put
people to sleep with charts and
graphs.”
- Dr. Mark Johnson
In testimony before the
House Judiciary Committee
on the spread of HIV
“Epidemiologists . . .
Are like bookies of disease, stalking the globe to determine
point-spreads on which groups of people are most likely to
get which diseases.
Part detective and part statistician, part anthropologist and
part physician, epidemiologists hope to track down the
agents of illness by deducing which of the differences
between peoples lie at the root of their distinctive disease
patterns.”
(H. Shodell, Science ’82, September, p. 50)
Functions of Epidemiology
(Schoenback and Rosamond)
Epidemiologic approaches
DESCRIPTIVE
Health and disease in the community
What?
Who?
When?
Where?
What are the
health problems
of the
community?
How many people
are affected?
Over what
period of time?
Where do the
affected people
live, work or
spend leisure
time?
What are the
attributes of
these illnesses?
ANALYTIC
Why?
What are the
causal agents?
What factors
affect outcome?
What are the
attributes of
affected persons?
Etiology, prognosis and program evaluation
How?
By what mechanism
do they operate?
Forms of Epidemiology
•Clinical Epidemiology
•Descriptive Epidemiology
•Predictive Epidemiology
•Etiologic Epidemiology
•Genetic Epidemiology
•Occupational Epidemiology
•Social Epidemiology
•Spatial Epidemiology
•Surveillance
etc…
Academia
The Colorado School of Public Health
US Accredited Schools of
Public Health, 2007
As of July 1st!
Government Agencies
•Local health departments
•State health departments
•Office of the Surgeon General of the United States
•FDA
•Centers for Disease Control (CDC)
Julie Gerberding, MPH, MD
•World Health Organization (WHO)
Industry
•Occupational epidemiologists – monitor and investigate effects of
worker exposures
•Pharmaceutical companies – mostly clinical trials of drugs, but also
follow-up epidemiologic studies
•Contract research organizations (CRO)– design and implement
epidemiologic studies for government or other industries
A Brief History of “Modern” Epidemiology
John Snow (1813-1858)
Public Health intervention
Late 1800s -> 1950s
The “hey day” of infectious disease
epidemiology and prevention
John Ryle (1899-1950)
The Institute of Social Medicine
Doll & Hill (1954)
Smoking and Lung Cancer
Archie Cochrane (1909-1988)
Evidence-based medicine
Mary-Claire King (1946- )
BRCA1 gene and Breast Cancer
What is Epidemiology?
The study of the distribution and determinants
of health and disease related states in
populations,
and the application of this study to control
health problems.
(John M. Last)
What are “disease” and “health”?
Dorland's Illustrated Medical Dictionary (28th ed.):
Disease – "any deviation from or interruption of the normal
structure or function of any part, organ, or system (or
combination thereof) of the body that is manifested by a
characteristic set of symptoms and signs . . .".
Health – "a state of optimal physical, mental, and social
well-being, and not merely the absence of disease and
infirmity."
What is “disease”
Manifestional criteria:
Manifestational criteria refer to symptoms, signs, and other
manifestations of the condition. Defining a disease in terms
of manifestational criteria relies on the proposition that
diseases have a characteristic set of manifestations. This
defines disease in terms of labeling symptoms.
Causal criteria:
Causal criteria refer to the etiology of the condition, which,
must have been identified in order to be employed. This
defines disease in terms of underlying pathological etiology.
Manifestational Criteria
The Acquired Immunodeficiency Syndrome (AIDS) was
initially defined by the CDC in terms of manifestational criteria
as a basis for instituting surveillance.
The operational definition grouped diverse manifestations –
Kaposi's sarcoma outside its usual subpopulation, PCP and
other opportunistic infections in people with no known basis
for immunodeficiency.
This was based on similar epidemiologic observations (similar
population affected, similar geographical distribution) and a
shared type immunity deficit (elevated ratio of T-suppressor to
T-helper lymphocytes).
Causal Criteria
Human immunodeficiency virus (HIV, previously called
human lymphotrophic virus type III) was discovered and
demonstrated to be the causal agent for AIDS.
AIDS could then be defined by causal criteria.
Challenges with Disease Classifications
1. A single causal agent may have multiple clinical effects.
2. Multiple etiologic pathways may lead to apparently identical
manifestations, so that a manifestationally-defined disease
entity may include subgroups with differing etiologies.
3. Multi-causation necessitates a degree of arbitrariness in
assigning a causative versus a contributing factor to a
disease.
4. Not all persons with the causal agent develop the disease.
The Natural History of Disease
onset of
disease
Physiologic
Abnormalities
Underlying
Genetic
Susceptibility
cause specific
mortality
diagnosis
of disease
Sub-clinical disease
Clinical disease
Environmental & Behavioral Factors
X
Measures of Disease Occurrence
• To study disease, need measures of its occurrence
• Some measures of disease occurrence
– Counts
– Prevalence
– Incidence
– Mortality
Epidemiologic approaches
DESCRIPTIVE
Health and disease in the community
What?
Who?
What are the
health problems
of the
community?
What are the
attributes of
these illnesses?
How many people
are affected?
What are the
attributes of
affected persons?
When?
Over what
period of time?
Where?
Where do the
affected people
live, work or
spend leisure
time?
Each of the measures can be calculated for different combinations
of “What? Who? When? and Where?”
Each of the W’s needs to be defined carefully to get comparable
measures across state, nation, world
Prevalence
• The prevalence of a disease is the proportion of individuals
in a population with disease (cases):
Number cases in population at specified time
Number of persons in population at that specified time
• Prevalence is a proportion – range of 0 to 1
• Removes the effect of total population size – makes
estimates from different populations or over time more
comparable.
Prevalence
• Often expressed as a percent (%) – Prevalence *100
• Also often expressed as the prevalence per 1,000 or 10,000 or
100,000.
• Prevalence * 1,000 = prevalence per 1,000.
Obesity Trends* Among U.S. Adults
BRFSS, 1991-2006
(*BMI ≥30, or ~ 30 lbs overweight for 5’ 4” woman)
1991
1995
2002
No Data
<10%
10%–14%
2006
15%–19%
20%–24%
≥25%
Prevalence – Salmonella
Cases infected with the outbreak strain of Salmonella Saintpaul,
as of July 15, 2008 9pm EDT
Incidence
• Incidence is a measure of risk of developing disease
Number of NEW cases in population DURING specified time
Number of persons AT RISK of disease in population during that specified time
• Often multiplied by 100,000 (or 1000 or 100) and reported as
“Incidence per 100,000”
If population size is
3.81 million, then
652
 100,000
3,810,000
 .00017 100,000
 17.1
I
Incidence – Salmonella
Incidence of cases of infection with the outbreak strain as of July 15,
2008 9pm EDT
Prevalence and Incidence – Salmonella
Cases infected with the outbreak strain of Salmonella Saintpaul,
as of July 15, 2008 9pm EDT
Incidence and Prevalence
• Incidence and prevalence measure different aspects of disease
occurrence
Prevalence
Incidence
Numerator:
All cases, no matter
Only NEW cases
how long diseased
Denominator
All persons in
population
Only persons at risk
of disease
Measures:
Presence of disease
Risk of disease
Most useful:
Resource allocation
Risk, etiology
Mortality Rate – Incidence of death
• Numerator
– Number of deaths
• Denominator
– Number of individuals in population
• Time interval
– 1-year: Annual Mortality Rate
– Typical to use annual rate
• Specifier
– age, sex, race, etc.
Mortality rates
Case Fatality “Rate”
• Cumulative incidence of death among those who
develop an illness
• Technically not a rate, but a proportion
• Time period should be stated
• Example
– 15/300 persons died in 30 days after surgery
– CFR = 0.05 x 1,000 = 50 per 1,000
– Risk of dying within 30 days of surgery is 50 per 1,000 surgeries, or
5%
Importance of defining numerator and
denominator
• For each of the measures, carefully defining both the
numerator and denominator crucial for interpretation
• In order for measures to be comparable across studies,
need consistent definition and reporting strategies for
numerator
• Also need consistent approaches for counting (or
estimating) the persons or person-time for the
denominator
Prevalence Numerator – case definition
From Gordis Text
Prevalence Numerator – case definition
AIDS cases, United States 1984-2000
Result of
new definition
1st Quarter of 1993:
Expansion of
surveillance case
definition
Gordis: Fig 4-17
Incidence Denominator – Who is at risk?
Importance of looking at multiple measures
The “demi” in Epidemiology
Understanding population dynamics is crucial to epidemiology.
Demography = the study of population dynamics including
fertility, mortality and migration
denominator…denominator…denominator…denominator…denominator…denominator…
Comparing rates between two different
populations
What is your guess regarding the incidence of HIV/AIDS in
Kenya compared to Denmark?
Comparing rates between two different
populations
Crude Incidence of HIV/AIDS, 2005
6
4
Rate / 1,000
2
0
Kenya
Denmark
Kenya data from UNAIDS/WHO, Denmark data from UNICEF
Comparing rates between two different populations
100
% of
cases
HIV/AIDS by Age
75
50
25
0
< 13
16
25
38
Age (years)
52
> 59
(from CDC, U.S. 2001-04)
Potential problems in interpretation of rates
over time
• Numerator
–
–
–
–
–
diagnostic abilities
diagnostic criteria
reporting completeness
payment schemes (affecting items above)
others . . .
• Denominator
–
–
–
–
census methods for classification
age misclassification
removal of persons at risk
cohort effects (changes in exposure/prognosis or other
confounding variables over time)
– others . . .
Age
/ Period
/ Cohort
Effects
Breast
Cancer Incidence
in Colorado
in 2000
Incidence of Breast Cancer (per 1,000)
50
40
30
20
10
0
20 - 29
30 - 39
40 - 49
50 - 59
60 - 69
Age (years)
70 - 79
80 - 89
Age / Period / Cohort Effects
Breast Cancer Incidence in Colorado by year of Survey
Incidence of Breast Cancer (per 1,000)
50
40
30
20
1910-19
1920-29
1930-39
1940-50
1950-59
10
0
20 - 29
30 - 39
40 - 49
50 - 59
60 - 69
Age (years)
70 - 79
80 - 89
The Three Epidemiology Modules
• Imperfect testing
• Pass it on
• Computer modeling of disease outbreaks
Imperfect Testing
Scientific questions that require or are made easier to answer by
binary tests
• Diagnosis of disease in a clinical setting
• Screening individuals to identify those who might need further
testing to determine disease status
• Surveillance for
- Cancer and other diseases
- Infectious disease outbreaks
- Bioterror agents
• Identifying sequence characteristics across the genome
Imperfect Testing
• Focus on medical testing, but applicable to all sorts of testing
scenarios
• Follows story of a woman who gets a positive mammogram and
wants to know the implications – does she have breast cancer?
• She goes on to get tested for some of the known breast cancer
genes – and learns what that means for her daughter
• Emphasis on understanding the implications of the results from
imperfect tests – and the personal decisions that are often
necessary.
• Uses simple and conditional probabilities and concepts of relative
risk (ratio of risk for those with and without genetic risk factor)
Pass it On/Modeling of Outbreak
Some questions we might want to ask about infectious disease
spread and epidemics
• How many individuals (or what proportion) will become infected?
• Will a given disease become epidemic? How far will it spread?
• How long will the disease or pathogen persist in the population?
• Would vaccination prevent an epidemic? If so, what type of
vaccination program is most efficient?
• What other measures could be taken to prevent an epidemic?
Pass it On
• Focus is on transmission of infectious disease
- explore routes of transmission
- probability of transmission based on a certain route or type of
contact
• Relates probabilities to expected numbers of exposed and infected
individuals
• Relate probabilities to evolutionary success of the disease-causing
organism
Computer Modeling of Disease Outbreaks
• Focus is on modeling characteristics of an outbreak
• Explores parameters expected to influence incidence and
prevalence of an infectious disease
• Uses a simple compartmental model
• Explores types of interventions and their impact on the parameters
that influence incidence, prevalence, scope of outbreak
The Three Epidemiology Modules
• Imperfect testing
• Pass it on
• Computer modeling of disease outbreaks