1. Measure of disease Dr Nadjarzadeh

2. 1/25/2011Incidence and prevalence2 The population perspective requires measuring disease in populations Science is built on classification and measurement. Reality is infinitely detailed, infinitely complex. Classification and measurement seek to capture the essential attributes.

3. 1/25/2011Incidence and prevalence3 Deriving meaning from stimuli Vase or faces? Which line is longer?

4. 1/25/2011Incidence and prevalence4 Measurement “captures” the phenomenon Classification and measurement are based on: 1.Objective of the classification 2.Conceptual model (understanding of the phenomenon) 3.Availability of data (technology)

5. 5/20/2002Incidence and prevalence5 O O O O O O O         An example population (N=200)

6. 1/25/2011Incidence and prevalence6         O How can we quantify disease in populations?

7. 1/25/2011Incidence and prevalence7         O O How can we quantify disease in populations?

8. 5/20/2002Incidence and prevalence8         O O O How can we quantify disease in populations?

9. 5/20/2002Incidence and prevalence9         O O O O O How can we quantify disease in populations?

10. 5/20/2002Incidence and prevalence10         O O O O O O How can we quantify disease in populations?

11. 1/25/2011Incidence and prevalence11         O O O O O O How can we quantify the frequency?

12. 1/25/2011Incidence and prevalence12         O O O O O O Rate of occurrence of new cases per unit time (e.g., 1 per month)

13. 5/20/2002Incidence and prevalence13         O 1 new case in month 1

14. 5/20/2002Incidence and prevalence14         O O 1 new case in month 2

15. 5/20/2002Incidence and prevalence15         O O O 1 new case in month 3, for a total of 3 cases

16. 5/20/2002Incidence and prevalence16         O O O O O 2 new cases in month 4

17. 5/20/2002Incidence and prevalence17         O O O O O O 1 new case in month 5 (total=6)

18. 5/25/2011Incidence and prevalence18         O O O O O O O 1 case in month 6

19. 5/20/2002Incidence and prevalence19         O O O O O O O O 1 new case in month 7

20. 5/20/2002Incidence and prevalence20         O O O O O O O O O O 2 new cases in month 8

21. 5/20/2002Incidence and prevalence21         O O O O O O O O O O O O 2 cases in month 9

22. 1/9/2007Incidence and prevalence22         O O O O O O O O O O O O Rate of occurrence of new cases during 9 months: 1 case/month to 2 cases/month

23. 1/9/2007Incidence and prevalence23 Number of cases depends on length of interval Divide by length of time interval, so can compare across intervals Number of new cases Rate of new cases = ––––––––––––––––– Time interval = 12 cases / 9 months = 1.33 cases / month

24. 1/25/2011Incidence and prevalence24 Number of cases depends on population size So, divide by population and time: Number of new cases Incidence rate = –––––––––––––––––– Population-time

25. 1/25/2011Incidence and prevalence25 How to estimate population-time? Population at risk: the people eligible to become a case and to be counted as one. In this example that population declines as each case occurs. So estimate population-time as...

26. 1/25/2011Incidence and prevalence26 Population-time = Method 1: Add up the time that each person is at risk Method 2: Add up the population at risk during each time segment Method 3: Multiply the average size of the population at risk by the length of the time interval

27. 1/9/2007Incidence and prevalence27 Estimating population-time - method 2 Total population-time over 9 months = 200 + 199 + 198 + 197 + 195 + 194 + 193 + 192 + 190 = 1,758 person-months = 146.5 person-years However, cases are not at risk for a full month.

28. 1/9/2007Incidence and prevalence28 Estimating population-time - method 2 - better Total population-time over 9 months = 199.5 + 198.5 + 197.5 + 196 + 194.5 + 193.5 + 192.5 + 191 + 189 = 1,752 person-months = 146 person-years assuming that cases develop, on average, in the middle of the month

29. 1/9/2007Incidence and prevalence29 Estimating population-time - method 3 Average size of the population at risk during the 9 months = 195.3 (1,758 / 9) or approximately: (200 + 188) /2 = 194 Population-time = 195.3 x 9 months or (approximately) 194 x 9 months = 1,746 person-months = 145.5 person-years

30. 1/9/2007Incidence and prevalence30 Equivalent to - method 3 Take initial size of population at risk and reduce it for time the people were not at risk due to acquiring the disease: 200 - 12/2 = 194 (approximately) Population-time = 194 x 9 months = 1,746 person-months = 145.5 person-years

31. 1/25/2011Incidence and prevalence31 Incidence rate (“incidence density”) Number of new cases ––––––––––––––––––––––––––––––– Avg population at risk × Time interval Number of new cases = –––––––––––––––––––– Population-time

32. 1/25/2011Incidence and prevalence32 O O O O O O O         What proportion of the population at risk are affected after 5 months?

33. 1/30/2004Incidence and prevalence33         O What proportion of the population is affected after 1 month? (1/200)

34. 5/20/2002Incidence and prevalence34         O O What proportion of the population is affected after 2 months? (2/200)

35. 5/20/2002Incidence and prevalence35         O O O What proportion of the population is affected after 3 months? (3/200)

36. 5/20/2002Incidence and prevalence36         O O O O O What proportion of the population is affected after 4 months? (5/200)

37. 1/9/2007Incidence and prevalence37         O O O O O O 6 / 200 = 0.03 = 3% = 30 / 1,000 in 5 months

38. 1/25/2011Incidence and prevalence38 Incidence proportion (“cumulative incidence”) Number of new cases 5-month CI = ––––––––––––––––––– Population at risk Incidence proportion estimates risk.

39. 1/25/2011Incidence and prevalence39 Incidence rate versus incidence proportion Incidence rate measures how rapidly cases are occurring. Incidence proportion is cumulative. When care only about the “bottom line” (i.e., what has happened by the end of given period): incidence proportion (CI).

40. 1/25/2011Incidence and prevalence40 Incidence rate versus incidence proportion If risk period is long (e.g., cancer), we usually observe only a portion. To compare results from studies with different length of follow-up, use incidence rate (IR) If risk period is short, we usually observe all of it and can use incidence proportion.

41. Incidence rate versus incidence proportion (rare disease, IR = 0.005 / month) 1/25/2011Incidence and prevalence41 (see spreadsheet at epidemiolog.net/studymat/)

42. Incidence rate versus incidence proportion (common disease, IR = 0.2 / month) 1/25/2011Incidence and prevalence42

43. 5/20/2002Incidence and prevalence43 Case fatality rate “Case fatality rate” (but it’s really a proportion) = proportion of cases who die (in a specified time interval) Like a “cumulative incidence of death” in cases [ “incidence rate of death” in cases = “termination rate” = 1/(average survival time)]

44. 1/30/2007Incidence and prevalence44 Mortality rate Number of deaths Mortality rate = ––––––––––––––––––––––––– ––– Population at risk × Time interval Number of deaths Annual mortality rate = –––––––––––––––––– –––– Mid-year population (x 1 yr)

45. 6/6/2002Incidence and prevalence45 Mortality rate (more notes) Number of deaths Mortality rate = ––––––––––––––––––––––––– ––– Population at risk × Time interval Number of deaths Annual mortality rate = ––––––––––––––––– – Mid-year population

46. 5/20/2002Incidence and prevalence46 Mortality rates versus incidence rates Mortality data are more generally available Fatality reflects many factors, so mortality rates may not be a good surrogate of incidence rates Death certificate cause of death not always accurate or useful

47. 1/9/2007Incidence and prevalence47 Prevalence – another important proportion Number of existing (and new) cases Prevalence = ––––––––––––––––––––––––––– –––– Population at risk

48. 5/20/2002Incidence and prevalence48         O O O O O O O 1 new case, 1 death

49. 5/20/2002Incidence and prevalence49         O O O O O O O O 1 new case, 1 new death

50. 5/20/2002Incidence and prevalence50         O O O O O O O O O O 2 new cases, no deaths

51. 5/20/2002Incidence and prevalence51         O O O O O O O O O O O O 2 new cases, 1 new death

52. 5/20/2002Incidence and prevalence52         O O O O O O O O O O O O What is the prevalence? (9 / 197)

53. 5/20/2002Incidence and prevalence53 Fine points... Who is “at risk”? Endometrial cancer? Prostate cancer? Breast cancer? Only women who have not had a hysterectomy? “Could” develop the condition + “would” be counted.

54. 5/20/2002Incidence and prevalence54 More fine points Age? Immunity? Genetically susceptible?

55. 5/20/2002Incidence and prevalence55 More fine points... How do we measure time? Are 10 people followed for 10 years the same as 100 people followed for 1 year? Aging of the cohort? Secular changes?

56. 9/22/2005, 9/8/2008Incidence and prevalence56 Fine points... Importance of stating units and scaling unless they are clear from the context – e.g., 120 per 100,000 person-years = 10 per 100,000 person-months – Hazards from lack of clarity

57. 1/30/2004Incidence and prevalence57 “You can never, never take anything for granted.” Noel Hinners, vice president for flight systems at Lockheed Martin Astronautics in Denver, concerning the loss of the Martian Climate Orbiter due to the Lockheed Martin spacecraft team’s having reported measurements in English units whiles the orbiter’s navigation team at the Jet Propulsion Laboratory (JPL) in Pasadena, California assumed the measurements were in metric units.

58. 5/20/2002Incidence and prevalence58 Relation of incidence and prevalence Prevalence depends on incidence Higher incidence leads to higher prevalence if duration of cases does not change. Limitation of the bathtub analogy – flow rate needs to be expressed relative to the size of the source Introducing a new analogy...

59. 9/23/2002Incidence and prevalence59

60. 5/20/2002Incidence and prevalence60 Populatio n at risk Existing cases Deaths, cures, etc.

61. 1/25/2011Incidence and prevalence61 Incidence, prevalence, duration of hospitalization Remote community of 101,000 people One hospital, patient census = 1,000 Steady state 500 admissions per week Prevalence = 1,000/101,000 = 9.9/1,000 IR = 500/100,000 = 5/1,000/week Duration Prevalence / IR = 2 weeks

62. 1/25/2011Incidence and prevalence62 Relation of incidence and prevalence Under somewhat special conditions, Prevalence odds = incidence × duration Prevalence incidence × duration (see spreadsheet at www.epidemiolog.net/studymat/)

63. 5/20/2002Incidence and prevalence63 Standardization When objective is comparability, need to adjust for different distributions of other determinants Strategy: Analyze within each subgroup (stratum) Take a weighted average across strata Use same weights for all populations (See the Evolving Text on www.epidemiolog.net)

64. 8/17/2009Incidence and prevalence64 Familiar example of weighted averages Liters of petrol per kilometer - differs for Interstate (0.050 LpK) and non-Interstate (0.100 LpK) driving. To compare different cars, can: Compare them for each type of driving separately (stratified analysis) Average for each car, using one set of weights (e.g., 80% Interstate, 20% non-Interstate) E.g. = 0.80 x 0.050 LpK + 0.20 x 0.100 LpK = 0.060 LpK

65. 8/17/2009Incidence and prevalence65 Comparing a Suburu and a Mazda Juan drives a Suburu 800 km on Interstate highways and 200 km on other roads. His car uses 0.050 LpK on Interstates and 0.100 LpK on other roads, for a total of 60 liters of petrol, an average of 0.060 LpK (60 L / 1000 km). His overall LpK can be expressed as a weighted average: (800/1000) x 0.050 LpK + (200/1000) x 0.100 LpK = 0.80 x 0.050 LpK + 0.20 x 0.100 LpK = 0.060 LpK

66. 8/17/2009Incidence and prevalence66 Comparing a Suburu and a Mazda Shizu drives her Mazda on a different route, with only 200 km on Interstate and 800 km on other roads. She uses 0.045 lpk on Interstate highways and 0.080 LpK on non-Interstate. She uses a total of 73 liters, or 0.073 LpK. Her overall LpK can be expressed as a weighted average: (200/1,000) x 0.045 LpK + (800/1,000) x 0.080 LpK = 0.20 x 0.045 LpK + 0.80 x 0.080 LpK =0.073 LpK

67. 8/17/2009Incidence and prevalence67 How can we compare their fuel efficiency?

68. 8/17/2009Incidence and prevalence68 Total fuel efficiency is not comparable because weights are different

69. 8/17/2009Incidence and prevalence69 By adopting a “standard” set of weights we can compare fairly

70. 8/17/2009Incidence and prevalence70 Comparing a Suburu and a Mazda Juan’s Suburu: = 0.60 x 0.050 LpK + 0.40 x 0.100 LpK =0.070 LpK Shizu’s Mazda: = 0.60 x 0.045 LpK + 0.40 x 0.080 LpK =0.059 LpK The choice of weights may often affect the results of the comparison.