Descriptive Epidemiology

Session 3, Part 1

Learning ObjectivesSession 3, Part 1

• Define descriptive epidemiology

• Calculate incidence and prevalence

• List examples of the use of descriptive data

OverviewSession 3, Part 1

• Prevalence and incidence

• Person, place, and time

Prevalence and Incidence

What is Epidemiology?

Purposes:• Study risk associated with exposures• Identify and control epidemics• Monitor population rates of disease and

exposure

Study of distribution and determinants of states or events in specified populations,

and the application of this study to the control of health problems

Epidemiologic Investigation

• To answer the questions:– Who?– What?– When?– Where?– Why?– How?

Descriptive vs. Analytic Epidemiology

Descriptive epidemiology Analytic epidemiology

• Who • Why

• What • How

• When

• Where

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

• Standard diagnostic criteria that must be fulfilled 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 and restrictions on person, place, and time

Example Case Definition:Cyclosporiasis

• Probable – A case that meets the clinical description and

that is epidemiologically linked to a confirmed case

• Confirmed – A case that meets the clinical description and

at least one of the criteria for laboratory confirmation as described above

Descriptive EpidemiologyWhat is the problem?

• Most basic: a simple count of cases– Useful for looking at the burden of disease– Not useful for comparing to other groups or

populations

County # of Salmonella casesA 120B 500

Pop. size1,500,0005,300,000

Prevalence

• The number of affected persons present in the population divided by the number of people in the population

# of casesPrevalence =

# of people in the population

Prevalence Example• In 2010, a US state reported an estimated 253,040

residents over 20 years of age with diabetes. The US Census Bureau estimated that the 2010 population over 20 in that state was 5,008,863.

Prevalence = 253,040

5,008,863

Prevalence Example• In 2010, a US state reported an estimated 253,040

residents over 20 years of age with diabetes. The US Census Bureau estimated that the 2010 population over 20 in that state was 5,008,863.

Prevalence = 253,040 = 0.051

5,008,863

• In 2010, 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 causes 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

# of new cases of disease over a specific period of time

Incidence = # of persons at risk of disease

over the specified period of time

Incidence ExampleA study is examining factors related to non-small cell lung cancer (NSCLC) in community-dwelling adults. During the study period, 77,719 adults aged 50-76 were followed, and 612 developed NSCLC.

612 Incidence =

77,719

Source: Slatore et al. BMC Cancer 2011, 11:22

Incidence ExampleA study is examining factors related to non-small cell lung cancer (NSCLC) in community-dwelling adults. During the study period, 77,719 adults aged 50-76 were followed, and 612 developed NSCLC.

612 Incidence = = 0.0079

77,719 • The one year incidence of non-small cell lung cancer

among adults aged 50-76 is 0.79%– Can also be expressed as 79 cases per 10,000 persons

aged 50-76

Source: Slatore et al. BMC Cancer 2011, 11:22

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 the disease

Prevalence and Incidence

Prevalence

= prevalent cases

Prevalence and Incidence

Old (baseline) prevalence

= prevalent cases = incident cases

New prevalence

Incidence

No cases die or recover

Prevalence and Incidence

= prevalent cases = incident cases = deaths or recoveries

Practice ScenarioA town has a population of 3600. In 2010, 400 residents of the town are diagnosed with a disease. In 2011, 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 2010? In 2011?• How would you calculate the incidence in 2011?

Practice Scenario Answers

• Population: 3600• 2010: 400 diagnosed with a disease• 2011: 200 additional diagnosed with the disease• No death, no recovery

Numerator

Denominator

Prevalence (2010)

4003600

11.1%

Prevalence (2011)

6003600

16.7%

Incidence (2011)

??

?

Practice Scenario Answers

• Population: 3600• 2010: 400 diagnosed with a disease• 2011: 200 additional diagnosed with the disease• No death, no recovery

Numerator

Denominator

Prevalence (2010)

4003600

11.1%

Prevalence (2011)

6003600

16.7%

Incidence (2011)

2003200

6.3%

Descriptive Epidemiology

Person, Place, Time

Who? Where? When? • 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– Age data are usually grouped –

intervals depend on type of disease / event

• May be shown in tables or graphs

• May look at more than one type of person data at once

SOURCE: Centers for Disease Control and Prevention, National Center for Health Statistics, National Health Examination Survey and National Health and Nutrition Examination Survey III 1988-1994 and 2007-2008

Person Data: Race/EthnicityPrevalence of obesity among men aged 20 years and over by race/ethnicity,

United States, 1988-1994 and 2007-2008

Person Data: Age

Reported abortions, by known age group and year --- selected states,* United States, 2005--2007Age group (yrs) 2005 2006 2007Abortion rate†<15 1.3 1.2 1.215--19 14.9 15.1 14.820--24 29.5 30.4 30.025--29 21.9 22.6 22.030--34 13.5 13.9 13.735--39 7.7 8.0 7.9≥40 2.6 2.7 2.7

SOURCE: MMWR Surveillance Summaries. http://www.cdc.gov/mmwr/preview/mmwrhtml/ss6001a1.htm

Person Data: Age and SexAge-specific cancer incidence rates, by sex

SOURCE: Wisconsin Cancer Incidence and Mortality Report, 1996, p. 26 http://s3.amazonaws.com/zanran_storage/dhs.wisconsin.gov/ContentPages/3730888.pdf

Person Data Limited by Age

Bathrooms, 85,630

Personal use items, 58,220

Yard / garden equipment,

41,780

Packaging and containers,

35,020

Housewares, 52,990

Home workshop

tools, 38,210

Sports, 57,120

SOURCE: http://www.cpsc.gov/library/foia/foia05/os/older.pdf

Emergency Room Visits for Consumer-product Related Injuries among the Elderly (65 years and older), 2002

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

Time Data: Day

SOURCE: http://www.dhhs.state.nc.us/docs/ecoli.htm

0

2

4

6

8

10

12

10/11 10/14 10/17 10/20 10/23 10/26 10/29 11/1 11/4 11/7 11/10

Num

ber o

f cas

es

Date of onset

Epi Curve for E.Coli Outbreak, n=108

Time Data: Year

SOURCE: Broome County, NY: http://www.gobroomecounty.com/clinics/lyme-disease

Time Data: Year

SOURCE: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5153a1.htm

Time Data: Week

SOURCE: http://www.cdc.gov/flu/weekly/weeklyarchives2010-2011/weekly34.htm

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

Place Data: State2010 Obesity by State

State % State % State % State %Alabama 32.2 Illinois 28.2 Montana 23.0 Rhode Island 25.5Alaska 24.5 Indiana 29.6 Nebraska 26.9 South Carolina 31.5Arizona 24.3 Iowa 28.4 Nevada 22.4 South Dakota 27.3Arkansas 30.1 Kansas 29.4 New Hampshire 25.0 Tennessee 30.8

California 24.0 Kentucky 31.3 New Jersey 23.8 Texas 31.0Colorado 21.0 Louisiana 31.0 New Mexico 25.1 Utah 22.5Connecticut 22.5 Maine 26.8 New York 23.9 Vermont 23.2Delaware 28.0 Maryland 27.1 North Carolina 27.8 Virginia 26.0District of Columbia

22.2 Massachusetts 23.0 North Dakota 27.2 Washington 25.5

Florida 26.6 Michigan 30.9 Ohio 29.2 West Virginia 32.5Georgia 29.6 Minnesota 24.8 Oklahoma 30.4 Wisconsin 26.3Hawaii 22.7 Mississippi 34.0 Oregon 26.8 Wyoming 25.1Idaho 26.5 Missouri 30.5 Pennsylvania 28.6  

SOURCE: CDC http://www.cdc.gov/obesity/data/trends.html

Place Data: State

SOURCE: http://www.cdc.gov/obesity/data/trends.html

Place Data: Individual Cases

SOURCE: http://www.cdc.gov/ncidod/EID/vol9no7/02-0653-G1.htm

Spot map of men who tested positive for HIV at time of entry into the Royal Thai Army, Thailand, November 1991–May 2000.

Place Data: Airplane Seat

SOURCE: Olsen, S.J. et al. N Engl J Med. 2003 Dec 18; 349(25):2381-2.

Summary

• Descriptive epidemiology describes:– What happened– The population it happened in– When it happened

• Descriptive epidemiology identifies populations at high risk, helps with allocation of resources, and provides a foundation for developing hypotheses

Summary

• Commonly used measures in descriptive epidemiology are prevalence and incidence

• The main characteristics of descriptive epidemiologic data are person, place and time

References and Resources• Centers for Disease Control and Prevention. Principles of Epidemiology.

3rd ed. Atlanta, Ga: Epidemiology Program Office, Public Health Practice Program Office; 1992.

• Gordis L. Epidemiology. 2nd ed. Philadelphia, Pa: WB Saunders Company; 2000.

• Gregg MB, ed. Field Epidemiology. 2nd ed. New York, NY: Oxford University Press; 2002.

• Hennekens CH, Buring JE. Epidemiology in Medicine. Philadelphia, Pa: Lippincott Williams & Wilkins; 1987.

• Last JM. A Dictionary of Epidemiology. 4th ed. New York, NY: Oxford University Press; 2001.

• McNeill A. Measuring the Occurrence of Disease: Prevalence and Incidence. EPID 160 Lecture Series. Department of Epidemiology, University of North Carolina at Chapel Hill School of Public Health; January 2002.

References and Resources• Morton RF, Hebel JR, McCarter RJ. A Study Guide to Epidemiology and

Biostatistics. 5th ed. Gaithersburg, Md: Aspen Publishers Inc; 2001. • Incidence vs. Prevalence. ERIC Notebook [serial online]. 1999:1(2).

Department of Epidemiology, University of North Carolina at Chapel Hill School of Public Health / Epidemiologic Research & Information Center, Veterans Administration Medical Center. Available at: http://cphp.sph.unc.edu/trainingpackages/ERIC/issue2.htm. Accessed March 1, 2012.

• Wisconsin Cancer Incidence and Mortality, 1996. Wisconsin Department of Health and Family Services; October 1998. Available at: http://s3.amazonaws.com/zanran_storage/dhs.wisconsin.gov/ContentPages/3730888.pdf. Accessed March 1, 2012.

• Slatore CG, Gould MK, Au DH, Deffebach ME, White E. Lung cancer stage at diagnosis: Individual associations in the prospective VITamins and lifestyle (VITAL) cohort. BMC Cancer. 2011;11:228.

References and Resources• Ogden CL, Carroll DL. Prevalence of Overweight, Obesity, and Extreme

Obesity Among Adults: United States, Trends 1960-1962 Through 2007-2008. Centers for Disease Control and Prevention / National Center for Health Statistics, Division of Health and Nutrition Examination Surveys; June 2010. Available at: http://www.cdc.gov/NCHS/data/hestat/obesity_adult_07_08/obesity_adult_07_08.pdf. Accessed March 1, 2012.

• Abortion Surveillance --- United States, 2007. MMWR Surveillance Summaries. 2011;60(ss01):1-39. Available at: http://www.cdc.gov/mmwr/preview/mmwrhtml/ss6001a1.htm. Accessed March 1, 2012.

• Torugsa K, Anderson S, Thongsen N, et al. HIV Epidemic among Young Thai Men, 1991-2000. Emerg Infect Dis [serial online]. 2003;9(7). http://www.cdc.gov/ncidod/EID/vol9no7/02-0653-G1.htm. Accessed March 1, 2012.

• Olsen SJ, Chang HL, Cheung TYY, et al. Transmission of the severe acute respiratory syndrome on aircraft. N Engl J Med. 2003;349:2381-2382.