1. Center for Surveillance, Epidemiology, and Laboratory Services Division of Health Informatics and Surveillance José Aponte/John Copeland Epi Info Team Epi Info TM Data Analysis using Visual Dashboard July 2015 Epi Info™ 7 Software for Public Health EIS Summer Course

2. Learning Objectives  After completing this section, the participant will be able to: o Read multiple data formats using Visual Dashboard o Familiarize with the Visual Dashboard workspace o Understand some of the basic data managing and manipulation features in Visual Dashboard o Generate Statistics using Frequencies, Cross Stratification of Variables, 2x2 Tables and Means o Save canvas files o Export data in multiple formats using the Visual Dashboard

3. Analysis In Epi Info™ 7  In Epi Info™, Analysis is a tool for manipulating, managing, and examining data.  Data can be selected, sorted, listed, or manipulated with a series of commands, functions, and operators.

4. Analysis In Epi Info™ 7  Two options for analysis in Epi Info™ 7 o Classic Analysis – mostly command based o Visual Dashboard (New) – point and click

5. Classic Analysis Looks and feels like the previous versions of Epi Info’s Analysis module; command-driven, powerful, and has many data management functions not found in the dashboard.

6. Visual Dashboard Point-and-click driven; designed to be simple to operate and work with, and to be able to generate results rapidly. No need to learn intricate command syntax.

7. Visual Dashboard and Gadgets  All analysis in the dashboard is done using ‘gadgets’  Gadgets are packaged programs that increase the functionality of Dashboard  Three permanent ‘gadgets’ appear on Dashboard by default: o Record Count gadget o Data Filtering gadget o Data Recoding and Formatting gadget  Additional gadgets may be added as needed

8. Visual Dashboard and Gadgets  Data Recoding and Formatting gadget o Left-hand side of screen o Used for creating and recoding variables  Data Filtering gadget o Right-hand side of screen o Used for selecting subset of data to analyze  Record count o Displayed at top of screen o Counts number of records under analysis

9. Visual Dashboard W/ Default Gadgets Record Count Data Recoding and Formatting Data Filtering

10. Gadgets Overview  Line list  Frequency  Means  MxN/2x2 Tables  Charts  Combined frequency  Matched pair case control  Linear regression  Logistic regression

11. Adding Gadgets Adding gadgets is easy; simply right- click on the dashboard canvas and select Add Analysis Gadget.

12. Data Filtering gadget  Allows selection criteria to be incorporated into the analysis  Applies to all gadgets in the canvas  Filtering can be done at the gadget level if user

13. Data Recoding and Formatting gadget  Multiple options for Recoding and Formatting data o With Recoded Value: (i.e. allows grouping of data for continuous variables or transformation of coding 1=Male, 2=Female). o With Conditional Assignment: assigns value to variable when condition(s) are met. o With Assigned Expression: assigns value of a variable or assigns the value of a numeric or text expression to a variable.

14. Data Recoding and Formatting gadget o With Simple Assignment: o Create a Group variable: take advantage of some of the features available

15. Visual Dashboard Instructor Demonstration

16. Mock Salmonella outbreak: Cohort Study Morgan County Courthouse (Built 1905), Madison, Georgia. Photo taken May 1982. Posted October 2008. Photo by Calvin Beale. http://webarchives.cdlib.org/sw1wp9v27r/http://ers.usda.gov/Briefin g/Population/Photos/ShowCH.asp?FIPS=13211Calvin Beale http://webarchives.cdlib.org/sw1wp9v27r/http://ers.usda.gov/Briefin g/Population/Photos/ShowCH.asp?FIPS=13211

17. Background In May 2012 in the small town of Madison, GA, the long awaited Acme Company picnic took place. Friends and family of employees attended the picnic. There were 150-200 people who attended the event. The event was catered by a local sandwich shop. The menu had the following choices for sandwiches: Peanut butter and jelly, Reuben, egg salad sandwich, ham and cheese, grilled chicken, and grilled cheese. Salad choices for each meal included Caesar salad, garden salad, or a chef salad. Potato chips were offered a side. Freshly-baked chocolate chip and peanut butter cookies were served as deserts for each meal order. Drink choices were either iced tea or water. Because the event had a large number of attendees, food and deserts were served at two different times (12 pm and 2 pm) to give the shop ample opportunity to make all of the dishes.

18. Background Over the next few days following the picnic, the Epidemiology department at the county health department became inundated with calls and faxed lab reports of several culture-confirmed Salmonella Enteritidis cases. Most cases were associated with the Acme Manufacturing Company. Because there was a sudden increase in salmonella cases over the weekend, an investigation into a potential outbreak was conducted. A roster of attendees was obtained and each person was contacted. A case was defined as any attendee of the Acme company picnic presenting with diarrhea, abdominal cramps, and/or fever within 72 hours of the picnic. A total of 90 cases met the case definition.

19. Visual Dashboard Instructor Demonstration #2

20. Scenario #2  Salmonella enterica subspecies IV  Associated with a potluck dinner  Case report form developed:  symptoms  other clinical features  possible exposures  A total of 64 cases were interviewed.

21. Variables  Laboratory o Lab confirmed?  Exposures o Turkey o Stuffing o Potato o Gravy o Cramps o Pasta salad o Dog, cat, reptile  Symptoms o Onset DateTime o Fever o Diarrhea o Vomiting o Cramps o Headache o Muscle ache o Stool/24 hr o Diarrhea hrs#  Demographics o Id o Age (years) o Sex

22. File Information  MS Excel 2007 dataset (.xlsx)  Use the Line Listing worksheet

23. Question #1  Determine Case Definition status for all cases based on the following:  Confirmed  Laboratory confirmed LABORATORYSALM=Y  Probable  self-reported Fever and Diarrhea (>= 3 loose stools, Within 24 hrs)  without lab FEVER=Y DIARRHEA=Y STOOLIN24_HR >= 3 DIARRHEAHOURS >= 24 LABORATORYSALM=N

24. Question #1  Possible  self-reported Fever  without lab FEVER=Y DIARRHEA=N OR DIARRHEA IS NULL STOOLIN24_HR < 3 OR STOOLIN24_HR IS NULL  Not a case  No Diarrhea DIARRHEA=N  Not laboratory confirmed LABORATORYSALM=Y

25. Question #2  Distribution of Symptoms by Case Definition  Diarrhea  Fever  Headache  Muscle ache  Cramps  Back ache  Joint pain  Vomiting

26. Question #3  Draw an Epi Curve  Using Onset DateTime field

27. File Information  MS Excel 2007 dataset (.xlsx)  Use the Exposures worksheet

28. Question #4  Create a new variable  Classify Confirmed and Probable cases as Ill  Possibly cases and Non-cases as Well  Establish the Risk Ratio for the following exposures:  Turkey  Potato  Stuffing  Pasta Salad  Dog

29. For more information please contact Centers for Disease Control and Prevention 1600 Clifton Road NE, Atlanta, GA 30333 Telephone: 1-800-CDC-INFO (232-4636)/TTY: 1-888-232-6348 Visit: www.cdc.gov | Contact CDC at: 1-800-CDC-INFO or www.cdc.gov/info The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Center for Surveillance, Epidemiology, and Laboratory Services Division of Health Informatics and Surveillance Questions?