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An example scenario where this technology would be useful is in an outbreak investigation. Many epidemiologists are familiar with the food borne outbreak in Oswego, New York, U.S.A. on April 18th, 1940. In this outbreak, 75 of the 80 people known to have been present at the pot-luck church supper were interviewed. A survey was created and interviews were conducted with participants to determine the source of the contamination. While the Oswego study focused on a single region, the significant value of data synchronization can be seen by expanding this scenario to where interviews and data entry are conducted in different localities. Therefore, imagine that the Oswego church supper was attended by residents of the Oswego county and four other neighboring counties: Jefferson, Lewis, Oneida, and Wayne. Imagine two epidemiologists are investigating this outbreak; an Epidemic Intelligence Service (or EIS) officer investigating the outbreak in Oneida county and another officer at the state health department investigating the other counties. After data synchronization, both investigators will have a clear picture of the spread of the illness over space and time and the actual cause of the outbreak.
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EPI INFO™ MESH4X ─SYNCHRONIZATION PROTOTYPE
David A. NitschkeProject Manager Epi Info™ Development Project
US CDC
December 18th, 2008—Atlanta, GA
Taha A. KassHout, MD, MSDirector, Health Informatics and Biosurveillance
InSTEDD
The Team
David Nitschke (Lead)Roger Mir Mark BerndtEnrique Nieves, MS
Taha KassHout, MD, MS (Lead)Eduardo (Ed) JezierskiJuan Marcelo TondatoDaniel CazzulinoPablo M. Cibraro
EPI INFO™ MESH4X ─SYNCHRONIZATION PROTOTYPEThe 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 nonill) 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
PointSource Outbreak
Staphylococcus aureus suspected pathogen based on 4.3 hr average incubation period
Vanilla ice cream suspected source of infection (highest foodspecific Attack Rate (AR) of 80%) 0
5
10
15
20
25
Cou
nt
18 Apr 40 19 Apr 40Date of Onset
Epidemic Curve
Original Scenario
OSWEGO—AN OUTBREAK OF GASTROINTESTINAL ILLNESS FOLLOWING A CHURCH SUPPER
OSWEGO—AN OUTBREAK OF GASTROINTESTINAL ILLNESS FOLLOWING A CHURCH SUPPER Provided mockup Georeferenced
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.
OUTBREAK INVESTIGATION FORM
THE PROTOTYPE: ARCHITECTURE
EPI INFO™ MESH4X ─SYNCHRONIZATION PROTOTYPEThe Demonstration…
OUTBREAK INVESTIGATION IN ONEIDA COUNTYOneida 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
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)
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).
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.
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.
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
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 18th and 19th
16 interviewers did not show any illness (Yellow pins)
Dr. Mir logged into EpiX 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…
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.
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
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
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.
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
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 18th and 19th
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.
DATA SYNCHRONIZATION BETWEEN ONEIDA COUNTY AND THE OTHER NEIGHBORING COUNTIESDr. Mir, Oneida County MO, received an EpiX 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
SYNCHRONIZING ONEIDA COUNTY DATA WITH THE OTHER COUNTIES
Dr. Nitschke evaluates the data in the cloud (State’s Data ready to be shared)
efore Synchronization: No data in the cloud (State’s Data ready to be shared)
fter Synchronization: Dr. Nitschke verifies that the State’s data is in the cloud (Total of 47 Records)
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
SYNCHRONIZING ONEIDA COUNTY DATA WITH THE OTHER COUNTIES
Dr. Mir evaluates the data in the cloud (State’s Data ready to be shared)
efore Synchronization: State’s available online Data (47 Records)
fter Synchronization: Dr. Mir has data for all other counties (Total of 75 Records)
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:\epiinfo\data\epiinfo.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.
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 19th
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 RECORDSDr. 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
ata 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 uptodate information
ata updated in the cloud (State’s available online data)
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 19th
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 CDCDr. 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
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 18th and 19th
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 Projecthttp://code.google.com/p/mesh4x
Discussion Grouphttp://groups.google.com/group/mesh4x
Q&A SESSION
THANK YOU!
David A. NitschkeProject Manager Epi Info™ Development Project
Centers for Disease Control and Prevention (CDC)
404.498.6272
DNitschke@cdc.gov
http://www.CDC.gov/EpiInfo
Taha A. KassHout, MD, MSDirector, Health Informatics and Biosurveillance
InSTEDD
kasshout@instedd.org
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
ote: Case Sensitive!
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