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Descriptive Epidemiology

Descriptive Epidemiology . Session 3, Part 1. Learning Objectives Session 3, Part 1. Define descriptive epidemiology Calculate incidence and prevalence List examples of the use of descriptive data. Overview Session 3, Part 1. Prevalence and incidence Person, place, and time.

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Descriptive Epidemiology

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  1. Descriptive Epidemiology Session 3, Part 1

  2. Learning ObjectivesSession 3, Part 1 • Define descriptive epidemiology • Calculate incidence and prevalence • List examples of the use of descriptive data

  3. OverviewSession 3, Part 1 • Prevalence and incidence • Person, place, and time

  4. Prevalence and Incidence

  5. 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

  6. Epidemiologic Investigation • To answer the questions: • Who? • What? • When? • Where? • Why? • How?

  7. Descriptive vs. Analytic Epidemiology

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. Prevalence • Useful for assessing the burden of disease within a population • Valuable for planning • Not useful for determining what causes disease

  16. 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

  17. Incidence Example A 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: Slatoreet al. BMC Cancer 2011, 11:22

  18. Incidence Example A 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: Slatoreet al. BMC Cancer 2011, 11:22

  19. 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

  20. Prevalence and Incidence Prevalence is a function of the incidence of disease and the duration of the disease

  21. Prevalence and Incidence Prevalence = prevalent cases

  22. Prevalence and Incidence New prevalence Incidence Old (baseline) prevalence No cases die or recover = prevalent cases = incident cases

  23. Prevalence and Incidence = prevalent cases = incident cases = deaths or recoveries

  24. Practice Scenario A 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?

  25. Practice Scenario Answers • Population: 3600 • 2010: 400 diagnosed with a disease • 2011: 200 additional diagnosed with the disease • No death, no recovery

  26. Practice Scenario Answers • Population: 3600 • 2010: 400 diagnosed with a disease • 2011: 200 additional diagnosed with the disease • No death, no recovery

  27. Descriptive Epidemiology Person, Place, Time

  28. 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

  29. 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

  30. Person Data: Race/Ethnicity Prevalence of obesity among men aged 20 years and over by race/ethnicity, United States, 1988-1994 and 2007-2008 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

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

  32. Person Data: Age and Sex Age-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

  33. Person Data Limited by Age Emergency Room Visits for Consumer-product Related Injuries among the Elderly (65 years and older), 2002 SOURCE: http://www.cpsc.gov/library/foia/foia05/os/older.pdf

  34. 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

  35. Time Data: Day SOURCE: http://www.dhhs.state.nc.us/docs/ecoli.htm

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

  37. Time Data: Year SOURCE: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5153a1.htm

  38. Time Data: Week SOURCE: http://www.cdc.gov/flu/weekly/weeklyarchives2010-2011/weekly34.htm

  39. 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

  40. Place Data: State SOURCE: CDC http://www.cdc.gov/obesity/data/trends.html

  41. Place Data: State SOURCE: http://www.cdc.gov/obesity/data/trends.html

  42. Place Data: Individual Cases Spot map of men who tested positive for HIV at time of entry into the Royal Thai Army, Thailand, November 1991–May 2000. SOURCE: http://www.cdc.gov/ncidod/EID/vol9no7/02-0653-G1.htm

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

  44. 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

  45. Summary • Commonly used measures in descriptive epidemiology are prevalence and incidence • The main characteristics of descriptive epidemiologic data are person, place and time

  46. 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.

  47. 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.

  48. 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.

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