An Introduction to Epi Info 6/7

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

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

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

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

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

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

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

Make View

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.

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”

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).

Enter Data

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

Analyze Data

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

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.

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

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

Analysis Output Commands Tree Program Editor

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

Graphics Two Examples

A Kaplan-Meier Survival Curve A Scatterplot

Some Useful Websites

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

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

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

Feel free to send an e-mail Thank you! Feel free to send an e-mail with any questions to: rowhani@stanford.edu