Gastroenteritis at a University in Texas

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Session IIIPart I

• Descriptive and Analytic Epidemiology

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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

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Todays 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

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Descriptive Epidemiology

• Prevalence and Incidence

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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

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What is Epidemiology?

• Looking to answer the questions
• Who?
• What?
• When?
• Where?
• Why?
• How?

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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

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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

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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

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Descriptive EpidemiologyWhat?

• 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
Black 119
White 497
Pop. size
1,450,675
5,342,532
http//www.vdh.virginia.gov/epi/Data/race03t.pdf
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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

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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

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Prevalence

• Useful for assessing the burden of disease within
  a population
• Valuable for planning
• Not useful for determining what caused disease

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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
• of new cases of disease over a
  specific period of time
• Incidence
• of persons at risk of disease
  over that specific period of time

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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.
• 7
• Incidence 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

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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

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Prevalence and Incidence

• Prevalence is a function of the incidence of
  disease and the duration of disease

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Prevalence and Incidence
Prevalence
prevalent cases
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Prevalence and Incidence
New prevalence
Incidence
Old (baseline) prevalence
No cases die or recover
prevalent cases
incident cases
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Prevalence and Incidence
prevalent cases
incident cases
deaths or recoveries
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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?

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Practice Scenario Answers

• Population 3600
• 2003 400 diagnosed with a disease
• 2004 200 additional diagnosed with the disease
• No death, no recovery

Numerator
Denominator
Prevalence (2003)
400
3600
11.1
Prevalence (2004)
600
3600
16.7
Incidence (2004)
200
3200
6.3
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Descriptive Epidemiology

• Person, Place, Time

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Descriptive EpidemiologyWho? 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

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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

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Data Characterized by Person
Overweight and obesity by age United States,
1960-2002
Overweight including obese, 20-74 years
Overweight, but not obese, 20-74 years
Obese, 20-74 years
Overweight, 6-11 years
Overweight, 12-19 years
1960-62
1963-65
1966-70
1971-74
1976-80
1988-94
1999-2002
Year
SOURCES Centers for Disease Control and
Prevention, National Center for Health
Statistics, National Health Examination Survey
and National Health and Nutrition Examination
Survey.
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Data Characterized by PersonPrimary and
Secondary Syphilis, US, 1996-2000
Age White, Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Black, Non-Hispanic Hispanic Hispanic Asian/Pacific Islander Asian/Pacific Islander American Indian/Alaska Native American Indian/Alaska Native
Group 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
TOTAL 30.5 153.8 64.9 231.0 23.8 97.9 2.5 10.4 2.0 10.9
http//www.cdc.gov/std/stats00/Tables/2000Table32A
.htm Data shown are /1,000
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Data Characterized by Person
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Data Characterized by PersonEmergency Room
Visits for Consumer-product Related Injuries
among the Elderly (65 years and older), 2002
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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

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Data Characterized by Time
http//www.dhhs.state.nc.us/docs/ecoli.htm
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Data Characterized by Time
http//www.hivclearinghouse.org/0Surveillance203r
d20Quarter20Report.pdf
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Data Characterized by Time
http//www.cdc.gov/mmwr/preview/mmwrhtml/mm5153a1.
htm
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Data Characterized by Time
http//www.health.qld.gov.au/phs/Documents/cdu/127
76.pdf
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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

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Children aged lt72 months for whom blood lead
surveillance data were reported to CDC and
children confirmed to have blood lead levels
(BLLs) gt10 µg/dL by state and year selected U.S.
sites, 19972001
http//www.cdc.gov/mmwr/preview/mmwrhtml/ss5210a1.
htm
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Data Characterized by Place
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Data Characterized by Place
Spot map of men who tested positive for HIV at
time of entry into the Royal Thai Army, Thailand,
November 1991May 2000.
http//www.cdc.gov/ncidod/EID/vol9no7/02-0653-G1.h
tm
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Data Characterized by Place
Source Olsen, S.J. et al. N Engl J Med. 2003
Dec 18 349(25)2381-2.