1. Descriptive Epidemiology According to Person, Place, and Time
Chapter 5
Descriptive Epidemiology According to Person, Place, and Time

2. Descriptive Epidemiology
Allows us to
Describe the extent of a public health problem according to person, place, and time
Communicate a public health problem using tables and graphs
Identify who is at greatest risk for selected health-related states or events
Use surveillance methods to monitor whether unusual health related states or events exist and evaluate public health intervention programs
Understand how descriptive epidemiology can provide clues as to the causes of disease

3. Person Descriptive data on person answers the “who” question
Descriptors often include
Age
Sex
Race/ethnicity
Marital and family status
Occupation
Education

4. Place Descriptive data by place addresses the “where” question
These data often involve comparisons between or among geographic regions, in groups before and after migration, and between twins raised in different settings

5. Time
Epidemiologic investigations range from hours to weeks, years to decades
Short-term disease incubation periods of a few hours can be as important to the epidemiologist as long-term latency periods for chronic diseases spanning decades
Another term used occasionally to describe time factors in epidemiology is temporal, which means time or refers to time-related elements or issues

6. Communicating health data and identifying who is at greatest risk
Tables and graphs summarize and describe data in a way that can be easily interpreted

7. Example

8. Example

9. Dependency Ratio
Population <15 and 65+ divided by the population 15-64
Multiply by 100 to express as %
Interpretation – “There are ___ dependents for every 100 people of working age.”

10. Dependency Ratio in the United States
2000 – 51%
There are 51 dependent people for every 100 people of working age
2025 – 61%
There are 61 dependent people for every 100 people of working age
2050 – 67%
There are 67 dependent people for every 100 people of working age

11. Types of Trends
Secular trends – represent long-term changes in health-related states or events
Short-term trends – usually brief, unexpected increases in health-related states or events
Cyclic trends – represent periodic increases and decreases in the occurrence of health-related states or events

12. Example of a Secular Trend

13. Surveillance
Medical
Public health

14. Public Health Surveillance
Implicit in descriptive epidemiology is the notion of public health surveillance
What is public health surveillance?
Systematic ongoing collection, analysis, interpretation, and dissemination of health data

15. Why Surveillance Data? Monitor As a result, we identify whether
Identify sudden changes in occurrence
Follow long-term trends and patterns
Identify changes in risk factors
As a result, we identify whether
A health problem exists
The problem is getting worse

16. Explanations
Some explanations for observed changes in the frequency and pattern of cases in a surveillance system, which are not due to changes in risk exposures, include
Inconsistent interpretation and application of the case definition
Change in the case definition
Change in surveillance system/policy of reporting
Improved diagnosis (e.g., new laboratory test, increased physician awareness, a new physician in town)
Change in diagnostic criteria
Change in reporting requirements
Change in the population
Change in the level and emphasis on active case detection
Random events
Increased public awareness

17. Surveillance for Evaluation
Health programs may be aimed at
Increasing vaccination levels
Reducing smoking
Increasing fruit and vegetable consumption
Increasing physical activity
Decreasing obesity
Increasing screening

18. Vaccine Preventable Disease
State public health officials monitor vaccine preventable disease rates
May signal that the vaccination program is not reaching specific at-risk populations
Monitoring rates by racial/ethnic groups; for example, may show that the increasing rate only exists among a given minority group
Do barriers exist related to culture, language, and access to care?
The vaccination program should then be altered to address these barriers

19. Value The value of a surveillance program is determined by
Whether appropriate actions have been taken to date as a result of information from the surveillance system
Whether the information has been used to make decisions and take action
Whether monitored prevalence of the outcome variable relates to the level and distribution of services available
Whether the information may be used in the future

20. Causal Insights from Descriptive Epidemiology
Plotting health-related states or events over time can give the epidemiologist insights into probable determinants of disease
If a disease occurs only in the summer, then that is when the epidemiologist searches for causal factors

21. Causal Insights from Descriptive Epidemiology
Studies involving geographic comparisons of disease frequency between groups, states, countries, migration studies, and twin studies have further yielded important insights into the respective roles genetic and environmental forces have on disease.

22. Final Thoughts
Confounding factors are always a threat in descriptive studies
Analytic epidemiologic studies are better for minimizing the threat of confounding
Nevertheless, descriptive studies are a good first step in the search for causes of health-related states or events