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Epidemiology Kept Simple

Epidemiology Kept Simple. Chapter 6 Incidence and Prevalence. Case Counts. Prevalence count = no. of cases at particular time Incidence count = no. of case onsets that accumulate over time. Inadequacy of Case Counts. Counts without context seldom useful in epi Convert count to ratios

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Epidemiology Kept Simple

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  1. Epidemiology Kept Simple Chapter 6 Incidence and Prevalence

  2. Case Counts • Prevalence count = no. of cases at particular time • Incidence count = no. of case onsets that accumulate over time

  3. Inadequacy of Case Counts • Counts without context seldom useful in epi • Convert count to ratios • Numerator – case count • Denominator – population “size”

  4. Types of Ratios Used in Incidence and Prevalence • Rates () • Change per unit time • Can be used to describe incidence • Proportions (p) • Mathematically distinct from rates • Can be used for incidence and prevalence • Odds (o) • Rarely used for descriptive purposes but are still used in some multivariate models

  5. Types of Populations • Closed = Cohorts • Opened = Dynamic

  6. Closed Populations • No immigration or emigration • Average age increases over time • Size decreases over time (with “die-off”)

  7. Open Populations • Dynamics • Inflow = immigration & birth • Outflow = emigration & death • Average age may increase, decrease, or stay the same • Size may increase, decrease, or stay the same • Stable (“stationary”) population = inflow balances outflow = maintains constant size and age structure over time

  8. § 6.2: Incidence Proportion • Synonyms: risk, cumulative incidence • Use in closed population only • Numerator = onsets • Denominator = no. @ risk • excludes those not capable of developing the condition

  9. Incidence Proportion (Illustration) • Recruit 1000 women aged 60 – 69 • 100 had hysterectomies before age 60 • 900 at risk of uterine cancer • Follow for 10 years • 10 develop uterine cancer • pincidence = 10 women / 900 women = .011 • Interpretation • Average risk • Estimated probability of developing disease • e.g., 10-year average risk in group is .0111 (1.1%)

  10. § 6.3: Incidence Rate • Synonyms: incidence density, person-time rate • Can be applied to open and closed populations • Numerator = onsets • Denominator = person-time @ risk

  11. Understanding Person-Time • One person observed for 1 year = 1 person-year • Two people observed for ½ year each = 1 person-year • Four people observed for ¼ year each = 1 person-year • 52 people observed for a week each = 1 person-year • etc. (ad nauseum)

  12. Summing Person-Time in a Cohort In figure below Person 1 has 25 years before death Person 2 has 50 years before death Person-time in cohort = 25 + 50 = 75 years Rate = 2 onsets / 75 years = .000267 onsets / year

  13. Interpretation of Incidence Rate • “Speed” • How quickly events develop in population • Inverse of expected waiting time • Let  represent rate and ê represent life expectancy • ê = 1 /  • e.g., mortality rate = .0266667 year-1 (prior slide) • ê = 1 / .0266667 year-1 = 37.5 years (average lifespan) • When disease rare (pincidence 5%), incidence pincidence • i.e., rate estimates risk for rare diseases

  14. Estimating Person-Time in an Open Population • Person-time  (average population size) × (time of observation) • Example • 2,391,630 deaths in US in 1999 • Average population size in 1999 = 272,705,815 • One year observation period

  15. Other Types of Epi Rates • The concept of rate can be applied to various risk units • Examples shown below and on pp. 133—134

  16. Prevalence • Proportion with condition at point or period of time • Example • Recruit 1000 women aged 60 – 69 • 100 had hysterectomies before age 60 • Prevalence of hysterectomy = 100 women / 1000 women = .1

  17. Interpretation of Prevalence • Prevalence = probability person selected at random has condition • c.f. to incidence proportion (probability person selected at random will develop condition over stated time)

  18. Dynamics of Prevalence (p. 185)

  19. Relation Between Incidence and Prevalence Rate assumes disease rare & steady- state e.g., if rate is .1 year-1 and average duration is 2 years, prevalence = .1 year-1 × 1 year = .2

  20. Use of Multiplier to Report Incidence and Prevalence • To report per m people, multiply by m • e.g. Report rate of 0.00877 year-1 “per 100,000” (m = 100,000) • 0.00877 year-1 × 100,000 = 877 per 100,000 person-years • e.g., Report prevalence of .1 “per 100 persons” • .1 × 100 = 10 per 100 persons • Reporting per m does not change the value • But makes it easier for lay public to understand

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