epidemiology the basics only n.
Skip this Video
Loading SlideShow in 5 Seconds..
Epidemiology The Basics Only… PowerPoint Presentation
Download Presentation
Epidemiology The Basics Only…

Loading in 2 Seconds...

play fullscreen
1 / 28

Epidemiology The Basics Only… - PowerPoint PPT Presentation

  • Uploaded on

Epidemiology The Basics Only…. Adapted with permission from a class presentation developed by Dr. Charles Lynch – University of Iowa, Iowa City. Epidemiology.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Epidemiology The Basics Only…' - fruma

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
epidemiology the basics only

EpidemiologyThe Basics Only…

Adapted with permission from a class presentation developed by Dr. Charles Lynch – University of Iowa, Iowa City

  • Study of the distribution and determinants of health-related states or events in specified human populations and the application of this study to control of health problems.
epidemiology objectives
Epidemiology Objectives
  • Identify etiology of disease
  • Determine extent of disease
  • Study natural history
  • Evaluate new modes of health care delivery and new preventive and therapeutic measures
  • Provide foundation for developing public policy
usual pattern of reasoning
Usual Pattern of Reasoning
  • Develop a hypothesis
  • Test the hypothesis on an exposed human population and include an appropriate comparison group
  • Systematically collect and analyze data to determine whether a statistical association exists
usual pattern of reasoning1
Usual Pattern of Reasoning
  • Assess validity of any observed statistical association by excluding possible alternative explanations such as
    • Chance (random error)
    • Bias (systematic error)
    • Confounding (effects of additional variables)
    • Describe interaction
usual pattern of reasoning2
Usual Pattern of Reasoning
  • Judge whether the observed association represents a cause-effect relationship between exposure and disease
validity definition


The degree to which a measurement or study reaches a correct conclusion

types of validity definitions
  • Internal: Do the results of an investigation accurately reflect the true situation of the study participants?
  • External (i.e., generalizability): Are the results of a study applicable to other populations?
internal and external validity
Internal and External Validity
  • Internal validity-
    • must be the primary study objective because you would not want to generalize an invalid result
epidemiologic study cycle
Epidemiologic Study Cycle

Descriptive Studies- data

aggregation and analysis

Analysis of results suggests further descriptive study

of hypotheses and new hypotheses

Analytic Studiesto

test hypotheses

Form hypothesis

types of studies
Types of Studies
  • Observational
    • Descriptive
      • Study of the amount and distribution of disease within a population by person, place, and time
    • Analytic
      • Study of the determinants of disease or reasons for relatively high or low frequency in specific groups
  • Undertaken when little is known of the epidemiology of a disease
  • Provides information on patterns of disease occurrence in populations by characteristics such as age, race, marital status, social class, occupation, geographic area, and time occurrence
  • Usually uses routinely collected data


  • Used to generate the hypothesis NOT test the hypothesis





Case report (describes single patient)

Case series (describes characteristics of a number of patients)

  • Designed to test causal hypotheses that usually have been generated from descriptive studies
  • Collection of new data
  • More definitive conclusions about causation
types of studies for testing hypotheses
Types of Studies for Testing Hypotheses


  • Cross-sectional
  • Case-Control
  • Cohort (prospective, retrospective

Intervention (experimental, clinical trials)


Sequence of Studies in Human Populations

Clinical Observations



Available Data

Case-Control Studies

Cohort Studies

Randomized Trials

clinical applications of various types of studies
Clinical Applications of Various Types of Studies

Type of StudyApplication to Clinical Practice

Etiologic Can risk be reduced among susceptible persons?

Diagnostic Can accuracy and timeliness of diagnosis be improved?

Prognostic Can prognosis be determined more definitively?

Therapeutic Can treatment be improved?

case reports
Case Reports
  • Describe the experience of a single patient
  • Generally provide detailed documentation of a unique medical occurrence
  • May lead to the generation of a new hypothesis
  • Traditionally, a common type of study published in medical journals
  • Chief limitation: Sample size of 1
case series
Case Series
  • Collections of individual case reports
  • Often used as an early means to identify the beginning or presence of an epidemic
  • May lead to the generation of a new hypothesis
  • Chief limitation: Lack of an appropriate comparison group
descriptive studies of population groups
Descriptive Studies of Population Groups
  • Also called
    • Correlational studies
    • Ecologic studies
    • Aggregate studies
  • Studies in which the unit of analysis is some aggregate of individuals rather than an individual person
chance definition of p value

CHANCEDefinition of P-value

The probability that an effect at least as extreme as that observed in a particular study could have occurred by chance alone, given that there is truly no relationship between exposure and disease.

chance p value
  • If p-value < 0.05: Since there is less than a 5% probability (1 in 20 chance) of observing a result as extreme as that observed due solely to chance, we generally consider the association between the exposure and disease to be statistically significant.
chance p value1
  • If p-value > 0.05 - by convention:
    • We generally consider that chance cannot be excluded as a likely explanation
    • Findings are stated to be not statistically significant at that level
bias definition


Any systematic error in the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s effect on the risk of disease.

confounding another type of bias


  • A variable that:
    • Is causally related to (or at least associated with) the disease under study (or, as often occurs in practice, serves as a proxy measure for unknown or unmeasured causes), and
    • Is associated with the exposure under study in the study population but is not a consequence of this exposure