[The Epi Info™ team: David Nitschke (lead) (left), Roger Mir (middle) and Mark Berndt (right). According to our imaginary scenario (where we extended the sample Oswego outbreak from 1940), David is the NY State epidemiologist, Roger is the Oneida county Medical Officer, and Mark is the CDC epidemiologist]
[The Epi Info™ ─ Mesh4x Synchronization Tool]
[Synchronization over over the Amazon EC2/S3 cloud (State’s available online data in the scenario)]
[Synchronization over SMS]
Here I show the maps before synchronization of data (one map for Oneida county (highlighted in pink) on the left and the rest of the counties on the right). After the synchronization was completed, both maps were identical as the counties now have similar data.
After the demonstration, we identified with US CDC a high priority list for next steps, including:
[The NCPHI leadership team: Les (left) and Enrique (right)]
Finally, on Behalf of InSTEDDers, I want to wish you Happy Holidays and a Happy New Year!I’m leading a collaborative project with US CDC to establish a proof of concept demonstrating the potential to synchronize data in disparate Epi Info™ installations over the cloud and Short Message Service (SMS) text messages using the tools and libraries of the Mesh4X project. The Epi Info™ team includes: David Nitschke (lead), Roger Mir and Mark Berndt. The InSTEDD team includes: Juan Marcelo Tondato, Daniel Cazzulino, Pablo M. Cibraro, and Eduardo (Ed) Jezierski.
[The Epi Info™ team: Roger Mir (left) and David Nitschke (lead) (right)]
US CDC Epi Info™ is a suite of tools for use by public health professionals in conducting outbreak investigations, managing databases for public health surveillance, and general database and statistics applications. With Epi Info™, physicians, nurses, epidemiologists, and other public health and medical workers can rapidly develop a questionnaire, customize the data entry and validation process, enter and analyze data. Epi Info™ offers adaptability to changing requirements, growing demands, and innovative and scalable public health solutions. Its language and localization features make it portable for national and international missions and events. And, it’s FREE, so developing countries with limited resources can also employ its power. Epi Info™ is now available as an Open Source project [Please see Official US CDC MMWR release notice].
While Epi Info™ is widely used around the world, its implementations have been limited to discrete stand alone applications with no collaborative, peer-to-peer exchange of data or internet connectivity. Data are exported and sent as discrete packets (databases or spreadsheets) to collaborating centers where the data are merged and analyzed. This is a time consuming process and presents a significant limitation especially during an outbreak investigation. This was an opportunity for us to work collaboratively with the US CDC National Center for Public Health Informatics (or NCPHI), directed by Dr. Leslie (Les) Lenert, and demonstrate the value of Mesh4x to meet this challenge.
Mesh4X is a light-weight synchronization platform developed by InSTEDD which provides libraries, tools and applications to simplify interoperability of different applications and services. Ed just posted a blog on the progress of Mesh4x and its various and interesting properties. During this prototype, we developed an adapter for Epi Info™ enabling near real-time data synchronization using the fastest available technology (Internet, wireless Internet, satellite communication, SMS, or flash drive/pen drive) that we believe to be of significant value to the public health community at large.
An example scenario where Mesh4x 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. 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, we recreated the outbreak as if the Oswego church supper was attended by residents of the Oswego county and four other neighboring counties: Jefferson, Lewis, Oneida, and Wayne. In this hypothesized scenario, we imagined two epidemiologists are investigating this outbreak; one investigating the outbreak in Oneida county and the other investigating the other counties. Prior to synchronization, Oneida county had inconclusive results on the cause of the outbreak (baked ham and Vanilla ice cream). After data synchronization, both investigators had a clear picture of the spread of the illness over space and time and concluded the actual source of the outbreak to be from the Vanilla Ice Cream prepared the night before the church supper on April the 18th. During this scenario, we also demonstrated synchronizing Google Earth maps between localities. We will be demonstrating the solution at the US CDC offices in Atlanta, GA next Thursday December 18th, I’ll keep you posted!
[Roger and David working on the User Interface]
Related Links:
Nico and I were invited to present at the 1st Workshop on Public Health Informatics organized by Center for Excellence for Biomedical and Public Health Informatics (BIOPHICS), Faculty of Tropical Medicine at Mahidol University in Bangkok, Thailand (Sep 29-Oct 10, 2008). The workshop was co-organized by University of Washington and the Rockefeller Foundation. This two-week workshop introduced the discipline of public health informatics to an elite group of public health and information technology experts from the MBDS and SEAMEO countries (Vietnam, Yunnan, Cambodia, Lao PDR, Myanmar, Indonesia, Philippines, Thailand, etc.) The course included topics on the application of latest advancements in information science and technology in supporting public health practice, education and research.
On Friday October 10, 2008, each country had a representative speaker from their group who presented on their country's current challenges in disease surveillance and response, what they learned from the workshop, and how best to apply that to address the current system's limitations and challenges.
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