1. GerstmanGerstmanChapter 21GerstmanChapter 21 Epidemiology Chapter 2 Causal Concepts

2. GerstmanGerstmanChapter 22 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 Hill’s Framework for Causal Inference

3. GerstmanGerstmanChapter 23GerstmanChapter 23 Natural History of Disease Progression of disease in an individual over time

4. GerstmanGerstmanChapter 24GerstmanChapter 24 Natural History of HIV/AIDS Identify stages: Susceptibility Subclinical Clinical

5. GerstmanGerstmanChapter 25Gerstman Chapter 25 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

6. GerstmanGerstmanChapter 26GerstmanChapter 2 6 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

7. GerstmanGerstmanChapter 27GerstmanChapter 27 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)

8. GerstmanGerstmanChapter 28GerstmanChapter 28 Types of Causes (Causal Pies) 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 A given disease can have multiple sufficient mechanisms

9. GerstmanGerstmanChapter 29GerstmanChapter 29 Causal Complement (Causal Pie) Causal complement ≡ the set of factors that completes a sufficient causal mechanism Example: tuberculosis –Necessary agent Mycobacterium tuberculosis –Causal complement “Susceptibility”

10. GerstmanGerstmanChapter 210GerstmanChapter 210 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? How does this concept apply to environmental and genetic causes of cancer? genetics trait yellow corn

11. GerstmanGerstmanChapter 211GerstmanChapter 211 Causal Web Causal factors act in a hierarchal web

12. GerstmanGerstmanChapter 212GerstmanChapter 212 Epidemiologic Triad Agent, host, and environmental interaction

13. GerstmanGerstmanChapter 213 Types of Agents (Table 2.2) BiologicalChemicalPhysical HelminthsFoodsHeat ProtozoansPoisonsLight / radiation FungiDrugsNoise BacteriaAllergensVibration RickettsiaObjects Viral Prion

14. GerstmanGerstmanChapter 214 Types of Host Factors Physiological Anatomical Genetic Behavioral Occupational Constitutional Cultural etc!

15. GerstmanGerstmanChapter 215 Types of Environmental Factors Physical, chemical, biological Social, political, economic Population density Cultural Env factors that affect presence and levels of agents

16. GerstmanGerstmanChapter 216 GerstmanChapter 2 16 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

17. GerstmanGerstmanChapter 217GerstmanChapter 217 Induction Sophisticated view of “incubation” needed when considering multicausality Induction = causal action to initiation Latency = disease initiation to detection Empirical induction period = induction + latency

18. GerstmanGerstmanChapter 218GerstmanChapter 218 Induction & Initiation Heart Disease Example

19. GerstmanGerstmanChapter 219 §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

20. GerstmanGerstmanChapter 220 Understanding causal mechanisms 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 Told ya’

21. GerstmanGerstmanChapter 221 Opposing View: Discovery of Preventive Measure May Predate Identification of Definitive Cause What if we waited until the mechanism was known before employing citrus?

22. GerstmanGerstmanChapter 222 1964 Surgeon General’s 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 General’s report]Link to Surgeon General’s report

23. GerstmanGerstmanChapter 223 Hill’s Inferential Framework 1.Consistency 2. Specificity 3. Temporality 4. Biological gradient 5. Plausibility 6. Coherence 7. Experimentation 8. Analogy * Hill, A. B. (1965). The environment and disease: association or causation? Proceedings of the Royal Society of Medicine, 58, 295-300. full textfull text A. Bradford Hill (1897–1991)

24. GerstmanGerstmanChapter 224 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

25. GerstmanGerstmanChapter 225 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

26. GerstmanGerstmanChapter 226 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)

27. GerstmanGerstmanChapter 227 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?

28. GerstmanGerstmanChapter 228 or this?

29. GerstmanGerstmanChapter 229 Element 5: Biological Gradient Increases in exposure dose  dose-response in risk

30. GerstmanGerstmanChapter 230 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

31. GerstmanGerstmanChapter 231 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.

32. GerstmanGerstmanChapter 232 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

33. GerstmanGerstmanChapter 233 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