EPI INFO™ ─ MESH4X SYNCHRONIZATION PROTOTYPE Taha A. Kass-Hout, MD, MS Director, Health Informatics and Biosurveillance InSTEDD David A. Nitschke Project Manager - Epi Info™ Development Project US CDC December 18 th , 2008—Atlanta, GA

The Team David Nitschke (Lead) Roger Mir Mark Berndt Enrique Nieves, MS Taha Kass-Hout, MD, MS (Lead) Eduardo (Ed) Jezierski Juan Marcelo Tondato Daniel Cazzulino Pablo M. Cibraro

David Nitschke (Lead)

Roger Mir

Mark Berndt

Enrique Nieves, MS

Taha Kass-Hout, MD, MS (Lead)

Eduardo (Ed) Jezierski

Juan Marcelo Tondato

Daniel Cazzulino

Pablo M. Cibraro

EPI INFO™ ─ MESH4X SYNCHRONIZATION PROTOTYPE The Scenario…

The Scenario…

OSWEGO—AN OUTBREAK OF GASTROINTESTINAL ILLNESS FOLLOWING A CHURCH SUPPER Oswego County, New York: 1940 80 people attended a church supper on 4/18/1940 75 people (ill and non-ill) interviewed 46 people who attended the supper suffered from gastrointestinal illness beginning 4/18/1940 and ending 4/19/1940 Investigation focus: church supper as source of infection Original Scenario

Oswego County, New York: 1940

80 people attended a church supper on 4/18/1940

75 people (ill and non-ill) interviewed

46 people who attended the supper suffered from gastrointestinal illness beginning 4/18/1940 and ending 4/19/1940

Investigation focus: church supper as source of infection

Point-Source Outbreak Staphylococcus aureus suspected pathogen based on 4.3 hr average incubation period Vanilla ice cream suspected source of infection (highest food-specific Attack Rate (AR) of 80%) OSWEGO—AN OUTBREAK OF GASTROINTESTINAL ILLNESS FOLLOWING A CHURCH SUPPER Original Scenario

Point-Source Outbreak

Staphylococcus aureus suspected pathogen based on 4.3 hr average incubation period

Vanilla ice cream suspected source of infection (highest food-specific Attack Rate (AR) of 80%)

OSWEGO—AN OUTBREAK OF GASTROINTESTINAL ILLNESS FOLLOWING A CHURCH SUPPER Provided mockup Geo-referenced information Added addresses for all 75 interviewees Expanded the scenario to include 4 counties (in addition to Oswego) Modified Scenario DISCLAIMER: All places used in the modified (imaginary) scenario are fictitious. Any similarity to real places is a coincidence.

Provided mockup Geo-referenced information

Added addresses for all 75 interviewees

Expanded the scenario to include 4 counties (in addition to Oswego)

OUTBREAK INVESTIGATION FORM

THE PROTOTYPE: ARCHITECTURE

EPI INFO™ ─ MESH4X SYNCHRONIZATION PROTOTYPE The Demonstration…

The Demonstration…

OUTBREAK INVESTIGATION IN ONEIDA COUNTY Oneida Medical Officer (Dr. Roger Mir) receives a call from local doctors about patients reporting to clinics with gastrointestinal illness. Dr. Mir launches an investigation and begins interviews.

Oneida Medical Officer (Dr. Roger Mir) receives a call from local doctors about patients reporting to clinics with gastrointestinal illness. Dr. Mir launches an investigation and begins interviews.

ANALYSIS OF OUTBREAK DATA Dr. Mir has returned to the office from the interviews and he wants to perform some preliminary analysis on the data. He launches the Epi Info™ Menu and opens the Analysis module to read and analyze the data Epi Info™ Command: READ epiinfo.mdb: viewOswego

Dr. Mir has returned to the office from the interviews and he wants to perform some preliminary analysis on the data. He launches the Epi Info™ Menu and opens the Analysis module to read and analyze the data

Epi Info™ Command: READ epiinfo.mdb: viewOswego

ANALYSIS OF OUTBREAK DATA In the output window, Dr. Mir finds a Record Count of 28. Frequencies County and ILL Epi Info™ Command: FREQ COUNTY ILL The results show that all 28 cases are in Oneida County (12 interviewees that were ILL and 16 that were NOT ILL)

In the output window, Dr. Mir finds a Record Count of 28.

Frequencies County and ILL

Epi Info™ Command: FREQ COUNTY ILL

The results show that all 28 cases are in Oneida County (12 interviewees that were ILL and 16 that were NOT ILL)

ANALYSIS OF OUTBREAK DATA First, Dr. Mir will create a 2 by 2 table of BAKED HAM by ILL. Epi Info™ Command: TABLES BAKEDHAM ILL The results show that BAKED HAM is significant (at P = 0.05 level).

First, Dr. Mir will create a 2 by 2 table of BAKED HAM by ILL.

Epi Info™ Command: TABLES BAKEDHAM ILL

The results show that BAKED HAM is significant (at P = 0.05 level).

ANALYSIS OF OUTBREAK DATA Dr. Mir also creates a 2 by 2 table for VANILLA by ILL. Epi Info™ Command: TABLES VANILLA ILL This results show VANILLA is also significant.

Dr. Mir also creates a 2 by 2 table for VANILLA by ILL.

Epi Info™ Command: TABLES VANILLA ILL

This results show VANILLA is also significant.

ANALYSIS OF OUTBREAK DATA Dr. Mir, having analyzed the data, he knows that there are at least two potential sources of the illness—BAKED HAM and VANILLA ICE CREAM.

Dr. Mir, having analyzed the data, he knows that there are at least two potential sources of the illness—BAKED HAM and VANILLA ICE CREAM.

GENERATE GOOGLE EARTH MAP In order to gain a perspective of the cases, Dr. Mir will create a KML file to display in Google Earth (map layers). To create the KML file, he launches the Epi Info™ Mesh4x tool and generates a local map as follows: Click the “Map Exchange” tab Specify the data source (EpiInfo.mdb) and the Oswego table Click the “Create Map” button and this will generate the KML file

In order to gain a perspective of the cases, Dr. Mir will create a KML file to display in Google Earth (map layers). To create the KML file, he launches the Epi Info™ Mesh4x tool and generates a local map as follows:

Click the “Map Exchange” tab

Specify the data source (EpiInfo.mdb) and the Oswego table

Click the “Create Map” button and this will generate the KML file

GENERATE GOOGLE EARTH MAP It takes Dr. Mir about 30 seconds to make the KML file. To show the map, Dr. Mir opens the Google Earth file generated by the Epi Info™ Mesh4x tool. The results map has 28 cases in Oneida county: 12 patients reported with GI illness ( Red pins ) between April 18 th and 19 th 16 interviewers did not show any illness ( Yellow pins )

It takes Dr. Mir about 30 seconds to make the KML file. To show the map, Dr. Mir opens the Google Earth file generated by the Epi Info™ Mesh4x tool.

The results map has 28 cases in Oneida county:

12 patients reported with GI illness ( Red pins ) between April 18 th and 19 th

16 interviewers did not show any illness ( Yellow pins )

Dr. Mir logged into Epi-X and discovered a discussion about an outbreak in his neighboring county of Oswego. He initiates a call to Dr. Nitschke (with the State Health Department) to further discuss the situation with him… NEXT STEP…

Dr. Mir logged into Epi-X and discovered a discussion about an outbreak in his neighboring county of Oswego. He initiates a call to Dr. Nitschke (with the State Health Department) to further discuss the situation with him…

OUTBREAK INVESTIGATION IN THE OTHER COUNTIES The NY State Epidemiologist requests an EIS officer (Dr. David Nitschke) to help investigate a GI outbreak that appears in the counties of Oswego, Lewis, Jefferson, and Wayne.

The NY State Epidemiologist requests an EIS officer (Dr. David Nitschke) to help investigate a GI outbreak that appears in the counties of Oswego, Lewis, Jefferson, and Wayne.

ANALYSIS OF OUTBREAK DATA Dr. Nitschke has returned to the office from the interviews in 4 counties and he wants to perform some preliminary analysis on the data. He launches the Epi Info™ Menu and opens the Analysis module to read and analyze the data Epi Info™ Command: READ epiinfo.mdb: viewOswego

Dr. Nitschke has returned to the office from the interviews in 4 counties and he wants to perform some preliminary analysis on the data. He launches the Epi Info™ Menu and opens the Analysis module to read and analyze the data

Epi Info™ Command: READ epiinfo.mdb: viewOswego

ANALYSIS OF OUTBREAK DATA In the Output window, Dr. Nitschke finds a Record Count of 47 across the 4 counties. Frequencies County and ILL Epi Info™ Command: FREQ COUNTY ILL

In the Output window, Dr. Nitschke finds a Record Count of 47 across the 4 counties.

Frequencies County and ILL

Epi Info™ Command: FREQ COUNTY ILL

ANALYSIS OF OUTBREAK DATA Dr. Nitschke creates a 2 by 2 table for VANILLA by ILL. Epi Info™ Command: TABLES VANILLA ILL This results show VANILLA is significant.

Dr. Nitschke creates a 2 by 2 table for VANILLA by ILL.

Epi Info™ Command: TABLES VANILLA ILL

This results show VANILLA is significant.

GENERATE GOOGLE EARTH MAP In order to gain a perspective of the cases, Dr. Nitschke will create a KML file to display in Google Earth (map layers). To create the KML file, he launches the Epi Info™ Mesh4x tool and generates a local map as follows: Click the “Map Exchange” tab Specify the data source (EpiInfo.mdb) and the Oswego table Click the “Create Map” button and this will generate the KML file

In order to gain a perspective of the cases, Dr. Nitschke will create a KML file to display in Google Earth (map layers). To create the KML file, he launches the Epi Info™ Mesh4x tool and generates a local map as follows:

Click the “Map Exchange” tab

Specify the data source (EpiInfo.mdb) and the Oswego table

Click the “Create Map” button and this will generate the KML file

GENERATE GOOGLE EARTH MAP It takes Dr. Nitschke about 30 seconds to make the KML file. To show the map, Dr. Nitschke opens the Google Earth file generated by the Epi Info™ Mesh4x tool. The results map has 47 records in the 4 counties: 33 patients reported with GI illness ( Red pins ) between April 18 th and 19 th 14 interviewers did not show any illness ( Yellow pins )

It takes Dr. Nitschke about 30 seconds to make the KML file. To show the map, Dr. Nitschke opens the Google Earth file generated by the Epi Info™ Mesh4x tool.

The results map has 47 records in the 4 counties:

33 patients reported with GI illness ( Red pins ) between April 18 th and 19 th

14 interviewers did not show any illness ( Yellow pins )

NEXT STEP… Dr. Nitschke just received a call from Dr. Mir and learned that Oneida county has 28 cases, but Dr. Mir is unable to conclude the source of the outbreak based on the information he has. So, they agree to share information.

Dr. Nitschke just received a call from Dr. Mir and learned that Oneida county has 28 cases, but Dr. Mir is unable to conclude the source of the outbreak based on the information he has. So, they agree to share information.

DATA SYNCHRONIZATION BETWEEN ONEIDA COUNTY AND THE OTHER NEIGHBORING COUNTIES Dr. Mir, Oneida County MO, received an Epi-X alert about reported illnesses in nearby counties. Dr. Mir calls Dr. Nitschke requesting data from the nearby counties. Dr. Mir is now working with Dr. Nitschke on synchronizing his information with the State.

Dr. Mir, Oneida County MO, received an Epi-X alert about reported illnesses in nearby counties. Dr. Mir calls Dr. Nitschke requesting data from the nearby counties. Dr. Mir is now working with Dr. Nitschke on synchronizing his information with the State.

SYNCHRONIZING ONEIDA COUNTY DATA WITH THE OTHER COUNTIES Dr. Nitschke launches the Epi Info™ Mesh4x tool and Sync data over the Amazon EC2/S3 cloud (State’s available online data) Select the Data Exchange tab and click Synchronize

Dr. Nitschke launches the Epi Info™ Mesh4x tool and Sync data over the Amazon EC2/S3 cloud (State’s available online data)

Select the Data Exchange tab and click Synchronize

SYNCHRONIZING ONEIDA COUNTY DATA WITH THE OTHER COUNTIES Dr. Nitschke evaluates the data in the cloud (State’s Data ready to be shared) Before Synchronization: No data in the cloud (State’s Data ready to be shared) After Synchronization: Dr. Nitschke verifies that the State’s data is in the cloud (Total of 47 Records)

Dr. Nitschke evaluates the data in the cloud (State’s Data ready to be shared)

SYNCHRONIZING ONEIDA COUNTY DATA WITH THE OTHER COUNTIES Dr. Mir launches the Epi Info™ Mesh4x tool and Sync data over the Amazon EC2/S3 cloud (State’s available online data) Select the Data Exchange tab and click Synchronize

Dr. Mir launches the Epi Info™ Mesh4x tool and Sync data over the Amazon EC2/S3 cloud (State’s available online data)

Select the Data Exchange tab and click Synchronize

SYNCHRONIZING ONEIDA COUNTY DATA WITH THE OTHER COUNTIES Dr. Mir evaluates the data in the cloud (State’s Data ready to be shared) Before Synchronization: State’s available online Data (47 Records) After Synchronization: Dr. Mir has data for all other counties (Total of 75 Records)

Dr. Mir evaluates the data in the cloud (State’s Data ready to be shared)

ANALYSIS OF OUTBREAK DATA: ALL COUNTIES Dr. Mir now has the data from the other counties. The State’s Database in the cloud will also have all the data from Oneida County. We see that Dr. Mir now has 75 cases across the 5 counties (46 ILL and 29 NOT ILL) Epi Info™ Command: READ ‘C:epiinfodataepiinfo.mdb’: viewOswego Epi Info™ Command: FREQ COUNTY ILL

Dr. Mir now has the data from the other counties. The State’s Database in the cloud will also have all the data from Oneida County.

We see that Dr. Mir now has 75 cases across the 5 counties (46 ILL and 29 NOT ILL)

Epi Info™ Command: READ ‘C:epiinfodataepiinfo.mdb’: viewOswego

Epi Info™ Command: FREQ COUNTY ILL

ANALYSIS OF OUTBREAK DATA: ALL COUNTIES Dr. Mir runs the analysis again Epi Info™ Command: TABLES VANILLA ILL The results show that BAKEDHAM is no longer significant and that VANILLA is clearly the potential source of the outbreak.

Dr. Mir runs the analysis again

Epi Info™ Command: TABLES VANILLA ILL

The results show that BAKEDHAM is no longer significant and that VANILLA is clearly the potential source of the outbreak.

GENERATE GOOGLE EARTH MAP The results map shows 75 cases across ALL counties 46 patients reported with GI illness ( Red pins ) between April 18 th and 19 th 29 interviewers did not show any illness ( Yellow pins ). Drs. Mir and Nitschke each launches Epi Info™ Mesh4x tool on their laptops and generate a local map for their respective counties (as previously described)

The results map shows 75 cases across ALL counties

46 patients reported with GI illness ( Red pins ) between April 18 th and 19 th

29 interviewers did not show any illness ( Yellow pins ).

Drs. Mir and Nitschke each launches Epi Info™ Mesh4x tool on their laptops and generate a local map for their respective counties (as previously described)

UPDATING RECORDS Dr. Nitschke receives a call about a new incident case from Lewis County. Upon further investigation, the previously not ill person is now ill because he ate Vanilla Ice Cream that he took home from the church supper.

Dr. Nitschke receives a call about a new incident case from Lewis County. Upon further investigation, the previously not ill person is now ill because he ate Vanilla Ice Cream that he took home from the church supper.

OUTBREAK INVESTIGATION FORM

OUTBREAK INVESTIGATION FORM Data updated in Epi Info™

SYNCHRONIZING NEW CASE Dr. Nitschke launches Epi Info™ Mesh4x tool Sync data over the Amazon EC2/S3 cloud (State’s online available data) Dr. Nitschke now also has data from the Oneida county Dr. Mir also launches Epi Info™ Mesh4x tool to get the update record Sync data over the Amazon EC2/S3 cloud (State’s online available data) Dr. Mir now has the most up-to-date information Data updated in the cloud (State’s available online data)

Dr. Nitschke launches Epi Info™ Mesh4x tool

Sync data over the Amazon EC2/S3 cloud (State’s online available data)

Dr. Nitschke now also has data from the Oneida county

Dr. Mir also launches Epi Info™ Mesh4x tool to get the update record

Sync data over the Amazon EC2/S3 cloud (State’s online available data)

Dr. Mir now has the most up-to-date information

GENERATE GOOGLE EARTH MAP The results map shows 75 cases across ALL counties 46 patients reported with GI illness ( Red pins ) between April 18th and 19 th 29 interviewers did not show any illness ( Yellow pins ) Patient19 status has changed to ill ( Red pin ) Drs. Nitschke and Mir each launches Epi Info™ Mesh4x tool on their laptops and generate a local map for their respective counties (as previously described)

The results map shows 75 cases across ALL counties

46 patients reported with GI illness ( Red pins ) between April 18th and 19 th

29 interviewers did not show any illness ( Yellow pins )

Patient19 status has changed to ill ( Red pin )

Drs. Nitschke and Mir each launches Epi Info™ Mesh4x tool on their laptops and generate a local map for their respective counties (as previously described)

SHARING DATA WITH CDC Dr. Mark Berndt, an epidemiologist at the CDC foodborne branch, is now involved in the investigation and wants to access State data

Dr. Mark Berndt, an epidemiologist at the CDC foodborne branch, is now involved in the investigation and wants to access State data

SHARING DATA WITH CDC Dr. Berndt launches the Epi Info™ Mesh4x tool and receives NY state’s data Select the Data Exchange tab and click Synchronize

Dr. Berndt launches the Epi Info™ Mesh4x tool and receives NY state’s data

Select the Data Exchange tab and click Synchronize

GENERATE GOOGLE EARTH MAP The results map shows 75 cases in NY state across 5 counties 47 patients reported with GI illness ( Red pins ) between April 18 th and 19 th 28 interviewers did not show any illness ( Yellow pins ). Dr. Berndt launches Epi Info™ Mesh4x tool on his desktop and generates a map for the state of NY (as previously described)

The results map shows 75 cases in NY state across 5 counties

47 patients reported with GI illness ( Red pins ) between April 18 th and 19 th

28 interviewers did not show any illness ( Yellow pins ).

Dr. Berndt launches Epi Info™ Mesh4x tool on his desktop and generates a map for the state of NY (as previously described)

The Tools Epi Info™ http://cdc.gov/epiinfo Epi Info™ - Community Edition http://www.codeplex.com/EpiInfo Mesh4x Project http://code.google.com/p/mesh4x Discussion Group http://groups.google.com/group/mesh4x

Epi Info™

http://cdc.gov/epiinfo

Epi Info™ - Community Edition

http://www.codeplex.com/EpiInfo

Mesh4x Project

http://code.google.com/p/mesh4x

Discussion Group

http://groups.google.com/group/mesh4x

Q&A SESSION

THANK YOU! David A. Nitschke Project Manager - Epi Info™ Development Project Centers for Disease Control and Prevention (CDC) 404.498.6272 [email_address] http://www.CDC.gov/EpiInfo Taha A. Kass-Hout, MD, MS Director, Health Informatics and Biosurveillance InSTEDD [email_address] http://www.instedd.org http://taha.instedd.org

David A. Nitschke

Project Manager - Epi Info™ Development Project

Centers for Disease Control and Prevention (CDC)

404.498.6272

[email_address]

http://www.CDC.gov/EpiInfo

Taha A. Kass-Hout, MD, MS

Director, Health Informatics and Biosurveillance

InSTEDD

[email_address]

http://www.instedd.org

http://taha.instedd.org

BACKUP SLIDERS

CREATE A MESH Go to: http://sync.staging.instedd.org:8080/mesh4x Example: http://sync.staging.instedd.org:8080/mesh4x/Epiinfo

CREATE A DATA FEED Go to: http://sync.staging.instedd.org:8080/mesh4x Example: http://sync.staging.instedd.org:8080/mesh4x

CLEAR DATA FROM A DATA FEED Go to: http://sync.staging.instedd.org:8080/mesh4x Example: http://sync.staging.instedd.org:8080/mesh4x/Epiinfo/test Note: Case Sensitive!