Epidemiology

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Epidemiology

• Chapter 2
• Causal Concepts

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Chapter 2
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Chapter Outline
2.1 Natural History of Disease Stages of
Disease Stages of Prevention 2.2 Variability
in the Expression of Disease Spectrum of
Disease The Epidemiologic Iceberg 2.3 Causal
Models Definition of Cause Component Cause
(Causal Pies) Causal Web Agent, Host, and
Environment 2.4 Causal Inference Introduction
Types of Decisions Philosophical
Considerations Report of the Advisory
Committee to the U.S. Surgeon General,
1964 Hills Framework for Causal Inference
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Natural History of Disease
Progression of disease in an individual over time
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Natural History of HIV/AIDS
Identify stages Susceptibility Subclinical Clinic
al
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Spectrum of Disease

• Most diseases demonstrate a range of
  manifestations and severities
• For infectious diseases, this called the gradient
  of infection
• Example Polio
• 95 subclinical
• 4 flu-like
• 1 paralysis

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Epidemiological Iceberg

• Only the tip of the iceberg may be detectable
• Dog bite example
• 3.73 million dog bites annually
• 451,000 medically treated
• 334,000 emergency room visits
• 13,360 hospitalizations
• 20 deaths

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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

Disease results from the cumulative effects of
multiple causes acting together (causal
interaction)
Ken Rothman (contemporary epidemiologist)
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Types of Causes (Causal Pies)
A given disease can have multiple sufficient
mechanisms

• Necessary cause found in all cases
• Contributing cause needed in some cases
• Sufficient cause the constellation of necessary
  contributing causes that make disease
  inevitable in an individual

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Causal Complement(Causal Pie)

• Causal complement the set of factors that
  completes a sufficient causal mechanism
• Example tuberculosis
• Necessary agent Mycobacterium tuberculosis
• Causal complementSusceptibility

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Yellow Shank Illustration

• Yellow shank disease (an avian disease) occurs
  only in susceptible chicken strains fed yellow
  corn
• What would the farmer think if he started feeding
  yellow corn to a susceptible flock?
• What would the farmer think if he added
  susceptible chickens to a flock being fed yellow
  corn?
• Is yellow shank disease an environmental or
  genetic disease?

genetics trait
yellow corn
How does this concept apply to environmental and
genetic causes of cancer?
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Causal Web
Causal factors act in a hierarchal web
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Epidemiologic Triad
Agent, host, and environmental interaction
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Types of Agents (Table 2.2)
Biological Chemical Physical
Helminths Foods Heat
Protozoans Poisons Light / radiation
Fungi Drugs Noise
Bacteria Allergens Vibration
Rickettsia Objects
Viral
Prion
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Types of Host Factors

• Physiological
• Anatomical
• Genetic
• Behavioral
• Occupational
• Constitutional
• Cultural
• etc!

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Types of Environmental Factors

• Physical, chemical, biological
• Social, political, economic
• Population density
• Cultural
• Env factors that affect presence and levels of
  agents

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Homeostatic Balance
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Induction

• Sophisticated view of incubation needed when
  considering multicausality
• Induction causal action to initiation
• Latency disease initiation to detection
• Empirical induction period induction latency

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Induction Initiation Heart Disease Example
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2.4 Causal Inference

• Causal inference ? the process of deriving
  cause-and-effect conclusions by reasoning from
  knowledge and factual evidence
• Proof is impossible in empirical sciences but
  causal statements can be made strong

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Understanding causal mechanisms
Told ya
Understanding causal mechanisms is essential for
effective public health intervention Consider the
case of miasmas and cholera (from Chapter 1) For
want of knowledge, efforts which have been made
to oppose cholera have often had contrary
effect. John Snow
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Opposing View Discovery of Preventive Measure
May Predate Identification of Definitive Cause
What if we waited until the mechanism was known
before employing citrus?
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1964 Surgeon Generals Report

• Epi data must be coupled with clinical,
  pathological, and experimental data
• Epi data must consider multiple variables
• Multiple studies must be considered
• Statistical methods alone cannot establish proof

Link to Surgeon Generals report
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Hills Inferential Framework

1. Consistency
2. Specificity
3. Temporality
4. Biological gradient
5. Plausibility
6. Coherence
7. Experimentation
8. Analogy

A. Bradford Hill (18971991)
Hill, A. B. (1965). The environment and
disease association or causation? Proceedings of
the Royal Society of Medicine, 58, 295-300. full
text
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Element 1 Strength

• Stronger associations are less easily explained
  away by confounding than weak associations
• Ratio measures (e.g., RR, OR) quantify the
  strength of an association
• Example An RR of 10 provides stronger evidence
  than an RR of 2

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Element 2 Consistency

• Consistency similar conclusions from diverse
  methods of study in different populations under a
  variety of circumstances
• Example The association between smoking and lung
  cancer was supported by ecological, cohort, and
  case-control done by independent investigators on
  different continents

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Element 3 Specificity

• Specificity the exposure is linked to a
  specific effect or mechanism
• Example Smoking is not specific for lung cancer
  (it causes many other ailments, as well)

Aristotle (384 322 BCE)
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Element 4 Temporality
Temporality exposure precedes disease in time
Mandatory, but not easy to prove. For example, is
the relationship between lead consumption and
encephalopathy this?
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or this?
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Element 5 Biological Gradient

• Increases in exposure dose ? dose-response in
  risk

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Element 6 Plausibility

• Plausibility appearing worthy of belief
• The mechanism must be plausible in the face of
  known biological facts
• However, all that is plausible is not always true

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Element 7 Coherence

• Coherence facts stick together to form a
  coherent whole.
• Example Epidemiologic, pharmacokinetic,
  laboratory, clinical, and biological data create
  a cohesive picture about smoking and lung cancer.

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Element 8 Experimentation

• Experimental evidence supports observational
  evidence
• Both in vitro and in vivo experimentation
• Experimentation is not often possible in humans
• Animal models of human disease can help establish
  causality

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Element 9 Analogy

• Similarities among things that are otherwise
  different
• Considered a weak form of evidence
• Example Before the HIV was discovered,
  epidemiologists noticed that AIDS and Hepatitis B
  had analogous risk groups, suggesting similar
  types of agents and transmission