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Organizing Epidemiologic Data

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  1. Organizing Epidemiologic Data

  2. Importance of Data Organization • Makes large data sets manageable • Allows for analysis • Relationships between disease and exposure • Trends • Communication

  3. Tables • Arranged in rows and columns • Can show patterns, trends, relationships or differences • Simplicity • Self-explanatory

  4. One-Variable Table • Frequency Distribution • 1st Column shows category • Sex = Male or Female • 2nd Column shows Number in each category • Can have additional columns • Percent • Cumulative percent

  5. Highest No of cases

  6. Intervention?

  7. Who to target?

  8. Two- and Three-Variable Tables • More in depth analysis • Be careful not to get to complicated • Look for associations • 3rd variable allows for stratification

  9. Ill Well Total Exposed Unexposed Total N Use of Two-By-Two Tables • Calculate association between disease and exposure a b c d ad/bc = Odd Ratio  Relative Risk

  10. Odd Ratio = 100 x 2340/89 x 811 = 234000/72179 OR = 3.24 Exercise 4.1B on page 212

  11. OR = 12 x 17/2 x 5 = 204/10 OR = 20.4 Answer to 4.1B

  12. Class intervals • May want to group data • Split variables into Categories • Age • Continuous (1, 2, 3, etc….) • Categorical (<1, 1-5, 6-10, etc….) • Watch out for overlap

  13. LaCrosse Age Groups

  14. Graphs/Charts • Shows data visually • Patterns, trends similarities and differences • Audience remembers • Many types • Line • Histogram • Bar • Pie

  15. Mapping • Use of Coordinates • Shows geographic location/distribution • Can be important in • Outbreak investigation • Health assessments • Intervention planning/evaluation

  16. Mapping in Rabies Control • Background on raccoon strain rabies in WV • Oral Rabies Vaccine Project (ORV) • Active Surveillance • Rabies Coordinates • Establishing the ORV barrier

  17. Benefits of Organizing Data • Summarizes large data sets • Displays Analysis • Visual representation of trends • Education • Funds • Increase knowledge

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