Transcript Gastroenteritis at a University in Texas

is for Epi
Epidemiology basics
for non-epidemiologists
Session III
Part I
Descriptive and Analytic
Epidemiology
Session Overview
1. Define descriptive epidemiology
2. Define incidence and prevalence
3. Discuss examples of the use of
descriptive data
4. Define analytic epidemiology
5. Discuss different study designs
6. Discuss measures of association
7. Discuss tests of significance
Today’s Learning Objectives
• Understand the distinction between
descriptive and analytic epidemiology, and
their utility in surveillance and outbreak
investigations
• Recognize descriptive and analytic
measures used in the epidemiological
literature
• Know how to interpret data for measures
of association and common statistical tests
Descriptive Epidemiology
Prevalence and Incidence
What is Epidemiology?
Study of the distribution and determinants
of states or events in specified
populations, and the application of this
study to the control of health problems
– Study risk associated with exposures
– Identify and control epidemics
– Monitor population rates of disease and
exposure
What is Epidemiology?
• Looking to answer the questions:
– Who?
– What?
– When?
– Where?
– Why?
– How?
Descriptive vs. Analytic
Epidemiology
• Descriptive epidemiology deals with the
questions: Who, What, When, and Where
• Analytic epidemiology deals with the
remaining questions: Why and How
Descriptive Epidemiology
• Provides a systematic method for
characterizing a health problem
• Ensures understanding of the basic
dimensions of a health problem
• Helps identify populations at higher risk for
the health problem
• Provides information used for allocation of
resources
• Enables development of testable
hypotheses
Case Definition
• A set of standard diagnostic criteria that
must be fulfilled in order to identify a
person as a case of a particular disease
• Ensures that all persons who are counted
as cases actually have the same disease
• Typically includes clinical criteria (lab
results, symptoms, signs) and sometimes
restrictions on person, place, and time
Descriptive Epidemiology
What?
• Addresses the question “How much?”
• Most basic is a simple count of cases
– Good for looking at the burden of disease
– Not useful for comparing to other groups or
populations
Race
# of Salmonella cases
Pop. size
Black
119
1,450,675
White
497
5,342,532
http://www.vdh.virginia.gov/epi/Data/race03t.pdf
Prevalence
• The number of affected persons present in
the population divided by the number of
people in the population
# of cases
Prevalence = ----------------------------------------# of people in the population
Prevalence Example
In 1999, a US state reported an estimated
253,040 residents over 20 years of age with
diabetes. The US Census Bureau estimated
that the 1999 population over 20 in that state
was 5,008,863.
253,040
Prevalence=
= 0.051
5,008,863
• In 1999, the prevalence of diabetes was 5.1%
– Can also be expressed as 51 cases per 1,000
residents over 20 years of age
Prevalence
• Useful for assessing the burden of disease
within a population
• Valuable for planning
• Not useful for determining what caused
disease
Incidence
• The number of new cases of a disease
that occur during a specified period of time
divided by the number of persons at risk of
developing the disease during that period
of time
Incidence =
# of new cases of disease over
a specific period of time
# of persons at risk of disease
over that specific period of time
Incidence Example
A study in 2002 examined depression among persons with
dementia. The study recruited 201 adults with dementia
admitted to a long-term care facility. Of the 201, 91 had
a prior diagnosis of depression. Over the first year, 7
adults developed depression.
Incidence =
7
= 0.064
110
• The one year incidence of depression among adults with
dementia is 6.4%
– Can also be expressed as 64 cases per 1,000
persons with dementia
Incidence
• High incidence represents diseases with
high occurrence; low incidence represents
diseases with low occurrence
• Can be used to help determine the causes
of disease
• Can be used to determine the likelihood of
developing disease
Prevalence and Incidence
• Prevalence is a function of the incidence
of disease and the duration of disease
Prevalence and Incidence
Prevalence
= prevalent cases
Prevalence and Incidence
New
prevalence
Incidence
Old (baseline)
prevalence
No cases die
or recover
= prevalent cases
= incident cases
Prevalence and Incidence
= prevalent cases
= incident cases
= deaths or recoveries
Practice Scenario
A town has a population of 3600. In 2003, 400
residents of the town are diagnosed with a
disease.
In 2004, 200 additional residents of the town are
diagnosed with the same disease. The disease
is lifelong but it is not fatal.
• How would you calculate the prevalence in
2003? In 2004?
• How would you to calculate the incidence in
2004?
Practice Scenario Answers
•
•
•
•
Population : 3600
2003: 400 diagnosed with a disease
2004: 200 additional diagnosed with the disease
No death, no recovery
Prevalence Prevalence Incidence
(2003)
(2004)
(2004)
Numerator
400
600
200
Denominator
3600
3600
3200
11.1%
16.7%
6.3%
Descriptive Epidemiology
Person, Place, Time
Descriptive Epidemiology
Who? When? Where?
Related to Person, Place, and Time
• Person
– May be characterized by age, race, sex,
education, occupation, or other personal
characteristics
• Place
– May include information on home, workplace,
school
• Time
– May look at time of illness onset, when
exposure to risk factors occurred
Person Data
• Age and Sex are almost always used in
looking at data
– Age data are usually grouped – intervals will
depend on what type of disease / event is
being looked at
• May be shown in tables or graphs
• May look at more than one type of person
data at once
Data Characterized by Person
Overweight and obesity by age: United States, 1960-2002
70
60
Percent
50
Overweight including obese, 20-74 years
40
Overweight, but not obese, 20-74 years
30
20
Obese, 20-74 years
Overweight, 6-11 years
10
Overweight, 12-19 years
0
1960- 1963- 1966
-70
65
62
197174
197680
Year
198894
19992002
SOURCES: Centers for Disease Control and Prevention, National Center for Health Statistics, National
Health Examination Survey and National Health and Nutrition Examination Survey.
Data Characterized by Person
Primary and Secondary Syphilis, US, 1996-2000
Age
Group
White, NonHispanic
Black, NonHispanic
Hispanic
Asian/Pacific
Islander
American
Indian/Alaska
Native
Male
Female
Male
Female
Male
Female
Male
Female
Male
Female
10-14
0.1
3.0
0.5
6.9
0.2
1.8
0.0
0.2
0.0
0.3
15-19
7.0
67.6
18.3
99.3
6.0
33.5
0.5
3.4
0.6
4.0
20-24
12.1
55.8
23.0
81.0
8.7
34.7
0.8
3.6
0.6
3.6
25-29
5.3
16.4
11.1
26.4
4.7
15.9
0.5
1.6
0.3
1.5
30-34
2.5
5.9
5.6
9.4
2.2
6.9
0.3
0.9
0.2
0.7
35-39
1.6
2.6
3.1
4.3
1.0
2.8
0.2
0.5
0.1
0.4
40-44
0.9
1.2
1.5
1.7
0.5
1.1
0.1
0.2
0.1
0.2
45-54
0.7
0.7
1.1
0.9
0.3
0.7
0.1
0.1
0.0
0.1
55-64
0.2
0.1
0.2
0.2
0.0
0.1
0.0
0.0
0.0
0.0
65+
0.1
0.2
0.1
0.2
0.0
0.1
0.0
0.0
0.0
0.0
30.5
153.8
64.9
231.0
23.8
97.9
2.5
10.4
2.0
10.9
TOTAL
http://www.cdc.gov/std/stats00/Tables/2000Table32A.htm Data shown are /1,000
Data Characterized by Person
Data Characterized by Person
Emergency Room Visits for Consumer-product Related
Injuries among the Elderly (65 years and older), 2002
Packaging and
containers,
35,020
Home
workshop
tools, 38,210
Yard / garden
equipment,
41,780
Housewares,
52,990
Bathrooms,
85,630
Personal use
items, 58,220
Sports,
57,120
Time Data
• Usually shown as a graph
– Number / rate of cases on vertical (y) axis
– Time periods on horizontal (x) axis
• Time period will depend on what is being
described
• Used to show trends, seasonality, day of
week / time of day, epidemic period
Data Characterized by Time
Epi Curve for E.Coli Outbreak, n=108
12
Number of cases
10
8
6
4
2
0
10/11 10/14 10/17 10/20 10/23 10/26 10/29
11/1
11/4
Date of onset
http://www.dhhs.state.nc.us/docs/ecoli.htm
11/7 11/10
Data Characterized by Time
http://www.hivclearinghouse.org/0Surveillance%203rd%20Quarter%20Report.pdf
Data Characterized by Time
http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5153a1.htm
Data Characterized by Time
http://www.health.qld.gov.au/phs/Documents/cdu/12776.pdf
Place Data
• Can be shown in a table; usually better
presented pictorially in a map
• Two main types of maps used:
choropleth and spot
– Choropleth maps use different
shadings/colors to indicate the count / rate of
cases in an area
– Spot maps show location of individual cases
Children aged <72 months for whom blood lead surveillance data were
reported to CDC and children confirmed to have blood lead levels
(BLLs) >10 µg/dL by state and year— selected U.S. sites, 1997–2001
http://www.cdc.gov/mmwr/preview/mmwrhtml/ss5210a1.htm
Data Characterized by Place
Data
Characterized by
Place
Spot map of men who tested
positive for HIV at time of
entry into the Royal Thai
Army, Thailand, November
1991–May 2000.
http://www.cdc.gov/ncidod/EID/vol9no7/020653-G1.htm
Data Characterized by Place
Source: Olsen, S.J. et al. N Engl J Med. 2003 Dec 18; 349(25):2381-2.