1. Introduction To Epidemiology
Mr. Manuel

2. What is Epidemiology?

3. Definition of Epidemiology
Last JM: A Dictionary of Epidemiology
The study of the distribution and determinants of health related states and events in populations and the application of this study to control of health problems

4. What Is The Unique Skill Of Epidemiologists?
Measuring disease frequency in populations

5. Measuring Disease Frequency Has Several Components
Classifying and categorizing disease
Deciding what constitutes a case of disease in a study
Finding a source for ascertaining the cases
Defining the population at risk of disease
Defining the period of time of risk of disease
Obtaining permission to study people
Making measurements of disease frequency
Relating cases to population and time at risk

6. Two Broad Types of Epidemiology
DESCRIPTIVE EPIDEMIOLOGY
ANALYTIC EPIDEMIOLOGY
Examining the distribution of a disease in a population, and observing the basic features of its distribution in terms of time, place, and person.
Typical study design:
community health survey (approximate synonyms - cross-sectional study, descriptive study)
Testing a specific hypothesis about the relationship of a disease to a putative cause, by conducting an epidemiologic study that relates the exposure of interest to the disease of interest.
Typical study designs: cohort, case-control

7. The Basic Triad Of Descriptive Epidemiology
THE THREE ESSENTIAL CHARACTERISTICS OF DISEASE WE LOOK FOR IN DESCRIPTIVE EPIDEMIOLOGY ARE:
PERSON
PLACE
TIME

8. Person (characteristics?)
Age
Gender
Socio-economic status (education, occupation, income)
Marital status
Ethnicity/race/genetic profile
Behavior / habits 8

9. Place (where ?)
Geographically restricted or widespread (outbreak, epidemic, pandemic)? Off-shore (tsunami…)
Climate effects (temperature, humidity, combined effects..)
Urban / sub-urban-squatter / rural  
Relation to environmental exposure
(water, food supply, etc)  
Multiple clusters or one? 9

10. Time (when ?) Changing or stable?
Clustered (epidemic) or evenly distributed (endemic)?
Time-trends: Point source, propagated, seasonal, secular, combinations 10

11. Data Collection Methods
Primary: where the investigator is the first to collect the data. Sources include: medical examinations, interviews, observations, etc. Pros: less measurement error, suits objectives of the study better.
Cons: costly, may not be feasible.
Secondary: where the data is collected by OTHERS, for other purposes that those of the current study.
Sources include: individual records (medical / employment); group records (census data, vital statistics)

12. Descriptive Epidemiology Is A Necessary Antecedent Of Analytic Epidemiology
To undertake an analytic epidemiologic study you must first:
Know where to look
Know what to control for
Be able to formulate hypotheses compatible with laboratory evidence

13. A common error in epidemiology is moving to analytic epidemiology without having a solid base in the descriptive epidemiology of the condition.

14. public health, because of the emphasis on disease prevention.
Epidemiologists are required to have some knowledge of the disciplines of the following:
public health, because of the emphasis on disease prevention.
clinical medicine, because of the emphasis on disease classification and diagnosis. 

15. pathophysiology, because of the need to understand basic biological mechanisms in disease.
statistics, because of the need to quantify disease frequency and its relationships to antecedents.
social sciences, because of the need to understand the social context in which disease occurs and presents.

16. Purposes Of Epidemiology
Identify causes and risk factors for disease.
Determine the extent of disease in the community.
Study natural history and prognosis of disease.
Evaluate preventive and therapeutic measures
Provide foundation for public policy

17. EVERY HEALTH OUTCOME HAS SOME INTERESTING AND USEFUL EPIDEMIOLOGIC CHARACTERISTIC
DEATH RATES BY SOCIAL CLASS FROM A CERTAIN CAUSE AMONG 1,316 PEOPLE
Men
Women
Children
Total
1st class
67% 3%
38%
2nd class
92%
14%
59%
3rd class
84%
54%
66%
62%
82%
26%
48%
WHAT CAUSE OF DEATH IS THIS?

18. The previous slide shows death rates by class of ticket on the Titanic, a large ocean liner that sank after colliding with an iceberg in 1912

19. Pandemic Influenza Phases
Time: Mondays and Wednesdays :10-5:20 p.m.
Office hours: BY ARRANGEMENT
Place: Room A -131 East Fee Hall
Department of Epidemiology classroom.
Person: Nigel Paneth, Instructor. ;

20. WHO phases of pandemic alert - Phase 4
Verified human-to-human transmission of an animal or human-animal influenza able to cause “community-level outbreaks.”
The ability to cause sustained disease outbreaks in a community.
Indicates a significant increase but not necessarily pandemic

21. Phase 5
Human-to-human spread of the virus into at least two countries in one WHO region. While most countries will not be affected at this stage
Is a strong signal that a pandemic is imminent and that the time to finalize the organization, communication, and implementation of the planned mitigation measures is short.

22. Phase 6 (pandemic phase)
Community level outbreaks in at least one other country in a different WHO region in addition to the criteria defined in Phase 5.
Indicate that a global pandemic is under way.

23. Differences Between Laboratory Sciences And Field Sciences
In the Field:
Mostly observational 
Variables controlled by nature 
Some variables unknown 
Replication difficult; exact replication impossible 
Results often uncertain 
Meaning of results for humans clear 
Statistical control often very important 
Highly labor intensive

24. Differences Between Laboratory Sciences And Field Sciences
In the Laboratory:
Mostly experimental
Variables controlled by the investigator
All variables known
Replication easy
Results valid
Meaning of results for humans uncertain.
Little need for statistical manipulation of data.
Highly equipment intensive

25. The Basic Triad Of Analytic Epidemiology
THE THREE PHENOMENA ASSESSED IN ANALYTIC EPIDEMIOLOGY ARE:
HOST
Define host, agent?
AGENT
ENVIRONMENT

26. Host
Age
Socio-economic status
Gender
Ethnicity/Race
Behavior

27. Host Factors
Genetic endowment
Immunologic state
Age
Personal behavior

28. Agent Living/Non-living Species Behavior Habitat
If the agent is human, gender, race etc. are factors
Examples: Nutrients, Poisons, Allergens, Radiation, Physical trauma, Microbes, Psychological experiences

29. Environment Crowding Atmosphere
Modes of communication – phenomena in the environment that bring host and agent together, such as:
Vector
Vehicle
Reservoir

30. Environment Geographically restricted or widespread (pandemic)?
Relation to water or food supply.  
Multiple clusters or one?

31. Analytic Epidemiology
Responses to this question vary. As outlined below, some believe that altruistically, society should pursue disease prevention to improve health and save money. These are noble goals, but I will demonstrate later that prevention does not always save money. The desire to prevent NCDs probably is a repercussion of our efforts to prevent infectious diseases. We have had great success in preventing communicable diseases. This has led to an initiative to prevent NCDs.

32. Study Development Process
Descriptive Studies: Data Collection and Analysis
Model Building and hypothesis formulation
Analyze results and retest
Analytic Studies for Hypothesis testing

33. Study Designs - Analytic Epidemiology
Experimental Studies
Randomized controlled clinical trials
Community trials
Observational Studies
Group data
Ecologic
Individual data
Cross-sectional
Cohort
Case-control
An Introduction to Epidemiology (CDC)

34. Experimental Studies
treatment and exposures occur in a “controlled” environment
planned research designs
clinical trials are the most well known experimental design. Clinical trials use randomly assigned data.
Community trials use nonrandom data
Experimental studies are stronger in determining the etiology of disease than descriptive studies

35. Observational Studies
non-experimental
observational because there is no individual intervention
treatment and exposures occur in a “non-controlled” environment
individuals can be observed prospectively, retrospectively, or currently

36. Cross-sectional studies
An “observational” design that surveys exposures and disease status at a single point in time (a cross-section of the population)
Cross section al studies are some of the first studies completed because of ease and low cost
time
Study only exists at this point in time

37. Cross-sectional Studies
Often used to study conditions that are relatively frequent with long duration of expression (nonfatal, chronic conditions)
It measures prevalence, not incidence of disease
Example: community surveys
Not suitable for studying rare or highly fatal diseases or a disease with short duration of expression
Cross-sectional studies involve point prevalence, not incidence. For very infrequent diseases they are of limited utility

38. Cross-sectional Design
factor present
No Disease
factor absent
Study
population
factor present
Disease
factor absent
Cross-sectional studies examine a point in time
time
Study only exists at this point in time

39. Epidemiologic Study Designs
Case-Control Studies
an “observational” design comparing exposures in disease cases vs. healthy controls from same population
exposure data collected retrospectively
most feasible design where disease outcomes are rare
Case-control studies in epidemiology are the most used type of study design

40. Case-Control Studies Cases: Disease Controls: No disease
Case-Control studies represent one form of analytic study that provides information on the relationship between causal factors and injuries. In a case-control study, subjects who have been injured are identified and their past exposure to suspected causal factors is compared with that of controls (persons who have not been injured).
Many case-control studies ascertain exposure from personal recall, using either a self administered questionnaire or an interview. The validity of such information will depend in part on the subject matter. People may be able to remember recent events quite well. On the other hand, long term recall is generally less reliable.
Source: Chapter 8: Case-control and cross-sectional studies, Epidemiology for the Uninitiated

41. Case-Control Studies Strengths Less expensive and time consuming
Efficient for studying rare diseases
Limitations
Inappropriate when disease outcome for exposure is not known at start of study
Exposure measurements taken after disease occurrence
Disease status can influence selection of subjects
Case control studies provide low cost answers to health questions.

42. Case-Control Design Study begins here factor present Cases (disease)
factor absent
Study
population
factor present
Controls
(no disease)
factor absent
Case-Control Design
present
past
time
Study begins here

43. Epidemiologic Study Designs
Cohort Studies
an “observational” design comparing individuals with a known risk factor or exposure with others without the risk factor or exposure
looking for a difference in the risk (incidence) of a disease over time
best observational design
data usually collected prospectively (some retrospective)
The cohort studies is the best for observational studies as the environmental event can be assessed before any disease outcome

44. Cohort Design Study begins here disease Factor present no disease
population
free of
disease
disease
Factor
absent
no disease
Cohort Design
present
future
A cohort studies follows a cohort of individuals who do not have disease, and then identified over time those individuals who have an outcome
time
Study begins here

45. Timeframe of Studies
Prospective Study - looks forward, looks to the future, examines future events, follows a condition, concern or disease into the future
Prospective cohort study
From Wikipedia, the free encyclopedia
time
Study begins here

46. Prospective Cohort study
Exposed
Outcome
Measure exposure
and confounder
variables
Non-exposed
Outcome
Baseline
Case-control studies are perhaps the most frequent form of analytic study design. These designs are very good for events that are rare in occurrence..
Still, there are some situations where cohort study designs would be appropriate in the field. The classic design in a cohort study is shown here. The study begins by assessing baseline levels of the exposure and other variables. Study subjects are then followed on a regular basis to identify the outcome. The frequency of outcomes are tested between persons who had exposure to the possible risk factor at baseline and persons with no exposure.
time
Study begins here

47. Timeframe of Studies
Retrospective Study - “to look back”, looks back in time to study events that have already occurred
time
Study begins here
Prospective vs. retrospective studies

48. Retrospective Cohort study
Exposed
Outcome
Measure exposure
and confounder
variables
Non-exposed
Outcome
Baseline
An alternative form of the cohort study is something termed the retrospective cohort study. Other researchers may also call this a historical prospective study. This design is nearly identical to the prospective cohort study. The sequence of baseline exposure determination and longitudinal follow-up for outcomes is similar. The difference lies in the time in which the study begins. In this retrospective design, the researcher constructs the cohort study by looking back in time and placing data in the appropriate order and sequence. These studies are possible to do with large medical databases, such as the membership files of the Health Maintenance Organizations, or the medical files in the Scandinavian countries.
time
Study begins here

49. Cohort Study Strengths
Exposure status determined before disease detection
Subjects selected before disease detection
Can study several outcomes for each exposure
Limitations
Expensive and time-consuming
Inefficient for rare diseases or diseases with long latency
Loss to follow-up
-- Exp. Measured before disease - so no temporal ambiguity
-- Exposure measured before disease - so disease cannot influence the amount of error with which exposure status is measured
-- Subject selection before disease, disease status does not influence of subjects

50. Experimental Studies investigator can “control” the exposure
akin to laboratory experiments except living populations are the subjects
generally involves random assignment to groups
clinical trials are the most well known experimental design
the ultimate step in testing causal hypotheses
Experimental studies are the ultimate form of design in assessing causality as there is random assignment to groups.

51. Experimental Studies
In an experiment, we are interested in the consequences of some treatment on some outcome.
The subjects in the study who actually receive the treatment of interest are called the treatment group.
The subjects in the study who receive no treatment or a different treatment are called the comparison group.
Experimental Studies

52. Epidemiologic Study Designs
Randomized Controlled Trials (RCTs)
a design with subjects randomly assigned to “treatment” and “comparison” groups
provides most convincing evidence of relationship between exposure and effect
not possible to use RCTs to test effects of exposures that are expected to be harmful, for ethical reasons
RCT should be conducted for hypotheses that have not been tested. Great care must be taken to evaluate possible negative outcomes as well as positive outcomes

53. Epidemiologic Study Designs
Randomized Controlled Trials (RCTs)
the “gold standard” of research designs
provides most convincing evidence of relationship between exposure and effect
trials of hormone replacement therapy in menopausal women found no protection for heart disease, contradicting findings of prior observational studies
It is not unexpected to find that observational studies find different results than for clinical trials. For example there have been 100s of observational studies demonstrating that hormone replacement was protective for women. However, when this was put to a clinical trail, the surprising result was that hormone replacement was not protective

54. Experimental Design time Study begins here (baseline point) outcome
RANDOMIZATION
Intervention
no outcome
Study
population
outcome
Control
no outcome
Experimental Design
baseline
future
Experimental and observational studies
A common goal for a statistical research project is to investigate causality, and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables or response. There are two major types of causal statistical studies: experimental studies and observational studies. In both types of studies, the effect of differences of an independent variable (or variables) on the behavior of the dependent variable are observed. The difference between the two types lies in how the study is actually conducted. Each can be very effective. An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements. In contrast, an observational study does not involve experimental manipulation. Instead, data are gathered and correlations between predictors and response are investigated.
From Wikipedia, the free encyclopedia
time
Study begins here (baseline point)

55. Randomized Controlled Trials
Disadvantages
Very expensive
Not appropriate to answer certain types of questions
it may be unethical, for example, to assign persons to certain treatment or comparison groups
Understanding controlled trials: Why are randomised controlled trials important? By Bonnie Sibbald and Martin Roland

56. Credits All information modified from these sources:
Nigel Paneth at the University of Pittsburgh
Thomas Songer, PhD - University of Pittsburgh Modified by Supercourse team
Ahmed Mandil, MBChB, DrPH Prof of Epidemiology High Institute of Public Health University of Alexandria
Understanding controlled trials: Why are randomised controlled trials important? By Bonnie Sibbald and Martin Roland