1. An Introduction to Epi Info 6/7

2. What is Epi Info?
A free public domain software package developed by the Centers for Disease Control and Prevention for the global community of medical and public health professionals.
It can be used to rapidly:
develop an electronic data entry form
enter data into this form
analyze data entered into this form or imported from other software packages

3. Past, Present, and Future
First version: Epi Info 1 (MS-DOS)
Released 1985
Latest version: Epi Info 3.5.1
Released 2008
Earlier this year, Epi Info became an “open source” software.
Epi Info 7

4. Worldwide use
A study conducted in 2003 documented at least 1 million downloads in at least 180 countries.
Epi Info has been translated to several languages by different institutions and individuals around the world. Examples include:
Spanish
Italian
Russian

5. Epi Info vs. other software packages
Epi Info has not been designed to replace:
Professional data management software packages such as:
Microsoft Access
FileMaker Pro
Professional data analysis software packages such as:
SAS
Stata R

6. Advantages of Epi Info Free User-friendly Point-and-click
All-in-one software
Design a data entry form, enter data, and analyze data
Time efficient
Very useful for outbreak investigations

7. Main applications in Epi Info
We will discuss these applications today:
Make View
For designing an electronic data entry form which automatically creates a data table
Enter Data
For entering data into the designed electronic data entry form
Analyze Data
For conducting a relatively wide range of statistical analysis of the data

8. Other applications in Epi Info
We will not discuss these applications today:
Create Maps (Epi Map)
For creating Geographic Information System (GIS) maps and overlaying survey data on to them
Create Reports (Epi Report)
For presenting results in a professional format
NutStat
A nutrition anthropometry program for calculating BMI and growth Z scores/percentiles

9. Make View

10. Make View
View is an electronic data entry form that you design based on a questionnaire used for primary data collection.
Each view has a corresponding data table “in the background”. No spreadsheet is involved.
There are 17 field (i.e., variable) types that you can choose from (Text, Number, Date, Time, Check Box, Yes/No, Option, etc.)
You can also add check codes and skip patterns to your view all by point-and-click.

11. What is a check code?
Check codes are rules and restrictions that you add to your view in order to improve the accuracy or efficiency of the data entry process. Examples include:
Making data entry for a particular variable required
Defining a range for a particular variable
Making a variable “Read Only”

12. An example of a view with fields grouped together and color-coded
Source: Epi Info tutorial
“Rhodococcal Infection After Open-Heart Surgery”
Based on a hospital outbreak investigation conducted by an EIS officer. The report was published in the New England Journal of Medicine (New Engl J Med 1991;324:104-9).

14. Enter Data

15. Enter Data You can easily:
enter data in the view that you have designed
control the order of data entry process
navigate through different records
find a particular or a group of records according to a criterion that you define

17. Analyze Data

18. Import/Export Data
You can import data generated in some other software packages
Text, Excel, dBASE, Access
You can export data suitable for use in some other software packages

19. Data manipulation
You can perform a relatively wide range of common data manipulation procedures such as:
Sorting data on a specific variable
Recoding categories of a variable
Defining a new variable
You can also merge records in one data table with those in another data table using a key (i.e., common) variable.

20. Statistical analysis (1)
Univariable analysis
Measures of central tendency and dispersion
Mean, median, mode, quartiles, standard deviation, etc.
Bivariable analysis
Chi-square and Fisher’s exact test
t test and the analysis of variance (ANOVA)
Odds ratio
Risk ratio
Risk difference

21. Statistical analysis (2)
Multivariable analysis
Linear regression
Logistic regression
Unconditional and conditional
Survival analysis
Kaplan-Meier
Cox proportional hazard regression
You can create dummy variables and interaction terms all by point-and-click
Complex sample survey analysis

22. Analysis Output
Commands Tree
Program Editor

23. Cross-tabulation of smoking and case/control status
An Example
Cross-tabulation of smoking
and case/control status

26. Graphics
Two Examples

27. A Kaplan-Meier Survival Curve
A Scatterplot

28. Some Useful Websites

29. CDC (http://www.cdc.gov/epiinfo)

30. User forum (http://cms.myepi.info)

31. North Carolina Center for Public Health Preparedness (Internet-based training)

32. Feel free to send an e-mail
Thank you!
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