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GerstmanChapter 21 Epidemiology Kept Simple Chapter 2 Causal Concepts.

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Presentation on theme: "GerstmanChapter 21 Epidemiology Kept Simple Chapter 2 Causal Concepts."— Presentation transcript:

1 GerstmanChapter 21 Epidemiology Kept Simple Chapter 2 Causal Concepts

2 GerstmanChapter 22 §2.1 Natural History of Disease Natural history of disease ≡ progression of disease in an individual over time.

3 GerstmanChapter 23 Natural History of HIV/AIDS Can you identify the subclinical stage?

4 GerstmanChapter 24 Definition of Cause Definition of “cause” Any event, act, or condition preceding disease or illness without which disease would not have occurred or would have occurred at a later time Ken Rothman (contemporary epidemiologist) Disease results from the cumulative effects of multiple causes acting together (causal interaction)

5 GerstmanChapter 25 Types of Causes Necessary – found in all cases Contributing – needed in some cases Sufficient–a constellation of causes that makes disease inevitable

6 GerstmanChapter 26 Causal Complement Causal complement = the set of factors that completes a sufficient mechanism Example: tuberculosis –Necessary agent Mycobacterium tuberculosis –Causal complement “Susceptibility”

7 GerstmanChapter 27 Epidemiological Iceberg Only the tip of the iceberg is easily observable Dog bite example –3.73 dog bites annually –451,000 medically treated –334,000 emergency room visits –13,360 hospitalizations –20 deaths

8 GerstmanChapter 28 Epidemiologic Spectrum Spectrum of illness - range of severities and manifestations Polio example –95%: subclinical –4%: flu-like symptoms –1%: polio paralysis

9 GerstmanChapter 29 Environment and genetics cannot be separated Yellow shank disease occurs only in susceptible chicken strains fed yellow corn What would a farmer think if he started feeding yellow corn to a susceptible flock? What would a [different] farmer think if he added susceptible chickens to a flock being fed yellow corn? Is yellow shank disease environmental or genetic? How does this apply to arguments about environmental and genetic causes of cancer?

10 GerstmanChapter 210 Causal Web Causal factors act in a hierarchal web MI causal web

11 GerstmanChapter 211 Epidemiologic Triad Agent, host, and environmental interaction HIV epi triad

12 GerstmanChapter 212 Homeostatic Balance E A H At equilibrium Steady rate E H A The proportion of susceptibles in population decreases Environmental changes that favor the agent E A H Environmental changes that favor the host E H A E A H Agent becomes more pathogenic

13 GerstmanChapter 213 Epi Variables Descriptive epidemiology looks at rates according to person, place, and time variables First step of investigation 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)

14 GerstmanChapter 214 “Rate” Loosely, the “rate” of an event is the number of events divided by population size

15 GerstmanChapter 215 Expression of Rate via “Population Multiplier” To express a rate with multiplier m, multiply by m Example: Let m = 1000  The rate of.00933 =.00933 × 1000 per 1000 = 9.33 per 1000. Example: Let m = 100,000  The rate of.00933 =.00933 × 100,000 per 100,000 = 933 per 100,000

16 GerstmanChapter 216 Person Variables Person variables are characteristics, attributes, and behaviors of individuals Examples of person variables are listed in Table 2.3 (p. 49) Surrogates for many health determinants Figure: Recreational injuries by age and gender; rates are per 1000 person-years

17 GerstmanChapter 217 Place Variables Place variables describe the locale where people live and work Examples of place variables are listed in Table 2.4 (p. 51) Differences may be due to genetic or environment Figure: Age-adjusted breast cancer mortality, 23 countries, 1958–59

18 GerstmanChapter 218 Time Variables Examples of time variables on p. 53 Epidemic curves - number of cases over time Figure illustrates: (A) Sporadic occurrence (B) Endemic occurrence (C) Point epidemic (D) Propagating epidemic

19 GerstmanChapter 219 Optional: Induction A sophisticated view of “incubation” needed when considering multicausality: incubation period broken into induction period and latent perio Induction = period between causal action and disease initiation Latency = period between disease initiation and disease detection Empirical induction period = induction + latency

20 GerstmanChapter 220 Induction & Initiation Heart Disease Example Genetic factors initiated at conception Environmental factors accumulate over lifetime Separate induction periods for G and E Latent period between disease initiation and detection


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