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Epidemiology Kept Simple

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Induction period = time between causal action and disease initiation. Latency period = time between disease ... Empirical induction period = induction latency ... – PowerPoint PPT presentation

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Title: Epidemiology Kept Simple


1
Epidemiology Kept Simple
  • Chapter 2
  • Causal Concepts

2
2.1 Natural History of Disease
  • Natural history of disease progression of
    disease in an individual over time
  • Disease defined loosely to refer to any form of
    morbidity or premature death
  • We consider
  • Single factor
  • Multiple causal factors

3
Stages in Natural History of Disease (Single
Cause)
  • Fig 2.1 (p. 34)

4
Natural History of HIV/AIDS
  • Fig 2.3 (p. 37)

5
Multiple Causal Factors
  • Causal factors rarely (if ever) act alone
  • Cause is the cumulative effects of multiple
    factors acting together
  • interdependence
  • interaction
  • multi-causality

6
Sophisticated view of incubation
  • Induction period time between causal action and
    disease initiation
  • Latency period time between disease initiation
    and detection
  • Empirical induction period induction latency

7
Natural History of Heart Attack (Genetic
Environmental Factors)
  • Fig 2.5 (p. 38)

8
2.2 Spectrum Iceberg
  • Every ailment has a broad range manifestations
    severities
  • We often see only the tip of the iceberg

9
2.3 Causal Concepts
  • What do we mean by cause?
  • There are several ways to define cause
  • Cause in a metaphysical concept
  • Rothman Greenlands (1998) definition
  • any event, act, or condition
  • precedes disease
  • without which disease would not have occurred or
    would have occurred at later time
    (counterfactual)

10
Sufficient / Component Cause (Causal Pies)
  • Necessary factor found in all of cases (e.g.,
    Mycobacteria exposure for TB)
  • Contributing factor unnecessary but combines
    with other factors to have an effect (e.g.,
    susceptibility to TB)
  • Sufficient cause is achieved when factors combine
    to make disease inevitable (Mycobacteria
    susceptible sufficient for TB)

11
Causal Pies Fig. 2.8 (p. 43)
12
Causal Complement
  • a factor or set of factors that complete a
    sufficient cause

13
Sufficient / Component Cause (cont.)
  • Interdependence factors working together in
    sufficient causal mechanism
  • completed pie
  • Helps understand complex epi concepts
  • e.g., What is the effect of a factor?
  • ANS The effect depends on prevalence of causal
    complements in the population
  • The effect of Mycobacterium exposure in a fully
    immune population is nil (increases risk by 0)
  • The effect of Mycobacterium exposure in a fully
    susceptible population is extreme (increases risk
    by 100)

14
Yellow Shank Metaphor
  • Yellow shank disease in chickens occurs only in
    susceptible strains feed yellow corn
  • What would the farmer think if you
  • Added yellow corn to the diet of a susceptible
    flock?
  • Added susceptible chickens to a flock feed yellow
    corn?
  • Now tell me, what causes cancer, environmental
    factors or genetic factors?

15
Another Model (Causal Web)
16
Causal Web Continued
  • Interdependence of cause at multiple levels
  • Macro (upstream)
  • Individual
  • Physiologic (downstream)

17
Still, another way to think about causality
(Agent, Host, Environment)
18
2.4 Epidemiologic Variables
  • Person
  • Place
  • Time

I keep six honest serving men (They taught me all
I know) Their names are what and why and
when And how and where and who. (Kipling)
19
Person Variables
  • Types of person variables (Table 2.3, p. 49)
  • Determines exposure and host susceptibility
  • Illustrative example Fig 2.13. (p. 50) Rate per
    1000 sports- and recreational injuries

20
Place
  • Host and environmental factors associated with
    place variables listed in Table 2.4 (p. 51)
  • Illustrative example (Regional Differences in
    Breast Cancer Mortality (Table 2.14, p. 52)
  • rate in U.S. 20 per 100,000 in 1962
  • rate in Japan 4 per 100,000 in 1962
  • rages in Japanese-Americans increases with each
    generation
  • reason is unclear see theories, p. 51

21
Time
  • Table 2.5 Examples of time variables
  • Fig 2.15

22
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