Epidemiology Flashcards
Study (scientific, schematic, data-driven) of the distribution (frequency and pattern) and determinants (causes, risk factors) of health-related stages or events in specified populations and the application to the control of health problems
Epidemiology
Epidemiology is concerned with two key factors of health events:
Frequency
Pattern
Number of health events (such as number of cases of meningitis or diabetes) but also to the relationship of that number to the size of the population
The rate allows epidemiologists to compare disease occurence across different populations
Frequency
Occurence of health related events by time, place and person
May be annual, seasonal, weekly, daily, hourly, weekday vs any other breakdown of time that may influence disease or injury occurence (time pattern)
Geographical variation, urban/rural differences, location of work site or schools (place pattern)
Pattern
Characterizing health events by time, place and person
Descriptive epidemiology
Any factor, whether event, characteristic or other definable entity, that brings about a change in health condition or other defined characteristic
Causes and other factors that influence the occurence of disease and other health-related events
Determinant
Anything that affects the well-being of a population
Health-related states or events
ex. disease
Concerned about collective health of the people in a community or population
Epidemiologist
Focuses on identifying the exposure or source that caused illness, number of persons similarly exposed; the potential for further spread in the community and interventions to prevent additional cases or recurrence
Explained disease from rarional rather than supernatural point of view
“On airs, waters and places”
Environmental and host factors such as behavior might influence development of disease
Hippocrates
Haberdasher and councilman who published a landmark analysis of mortality data in 1662
First to quantify patterns of birth, death and disease occurence noting disparities between males and females, high infant mortality, urban/rural differences and seasonal variations
John Graunt 1662
Father of modern vital statistics and surveillance
William Farr 1800
Anesthesiologist
Father of field epidemiology
Studied cholera outbreaks discovering cause and prevention of disease
Descriptive epi -> hypothesis generation -> hypothesis testing (analytic) -> application
John Snow
John Snow developed this tool showing the geographic distribution of cases
Spot map
Rotavirus vaccine SE
intusucception
Set of standard criterua for classifying whether a person has a particularly disease, syndrome or other health condition
Case definition
Graphing annual cases or rate of a disease over period of years
Long term
Secular trend
Disease occurence can be graphed by week or month over the course of a year or more to show its seasonal pattern
Seasonality
Suggests hypothesis about the time and source of exposure, the mode of transmission and causative agent
Uses histogram
Epidemic period
Single most important “person” attribute
Age
Key feature of analytic epidemiology
Comparison group
Quantifies the association between exposures and outcomes and to test hypotheses about casual relationships
Analytic epidemiology
Two kinds of analytic epidemiology
Experimental
Observational
Investigator determines through a controlled process the exposure for each indivdual (clinical trial) or community (community trial) and then tracks the individuals or communities over time to detect the effects of the exposure
Experimental studies
Epidemiologist simply observes the exposure and disease status of each participant
Observational studies
Observational study types:
Cohort
Case-control
Cross-sectional
Epidemiologist records whether each study participant is exposed or not and tracks to see if they develop disease
Investigator observes rather than determines participant’s exposure status (not randomly assigned)
After a period of time, the investigator compares the disease rate in rhe exposed group with the disease rate in unexposed
If the disease rare is substantively different in the exposed group compared to the unexposed group, the exposure is said to be associated with illness
Cohort study
Well known cohort study that established the rates and risk factors of heart disease
Framingham study
Participants enrolled as the study begins and are then followed prospectively over time to identify occurence of the outcomes of interest
Follow-up/Prospective Cohort
Both the exposure and the outcome have already occured
The investigator calculates and compares rates of disease in the exposed and unexposed groups
Used in investigations of disease in groups if easily identified people such as workers at a participar factor or attendees at a wedding
Retrospective cohort study
Investigators start by enrolling a group of people with disease and a comparison group (without disease)
Investigators compare previous exposures between the two groups
The control group provides an estimate of the baseline or expected amount of exposure in the population.
If the amount of exposure among the case group is substantially higher than the amount you would expect based on the control, then illness is said to be ASSOCIATED with that exposure
Case-Control
Sample of persons from a population is enrolled and their exposures and health outcomes are measured simultaneously
Assess the PREVALENCE of health outcome at that point of time without regard to duration
Weaker than either because it cannot disentangle risk factors for occurence of disease (incidence) from risk factors for survival with the disease
Synonymous to
Cross-sectional study
Survey
Prevalance rather than incidence
Subjects are enrolled or grouped on the basis of their exposure, then are followed to document occurence of disease
Difference in disease RATES between the exposed and unexposed groups lead investigators to conlcude that exposure is associated with disease
Cohort study