Showing posts with label Cloud Services. Show all posts
Showing posts with label Cloud Services. Show all posts

Sunday, May 22, 2011

From Tally Sticks, to Clouds, to .... Zombies

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Friday, July 9, 2010

Riff: A Social Network and Collaborative Platform for Public Health Disease Surveillance

From back of the napkin concept, to initial prototype and production, and finally to implementation, here is the story of Riff...
 

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Monday, December 22, 2008

Epi Info™ and Mesh4x Prototype Demonstration with US CDC

On Thursday, December 18th, 2008, we gave a joint theater-style demonstration of synchronizing Epi Info™ Data using Mesh4x with the Division of Integrated Surveillance Systems and Services (NCPHI/DISSS) at US CDC.

[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]


Here is a presentation and script scenario which walks you through the scenario step-by-step. You can download the latest Mesh4x tool from here, which also includes the sample data. [If you do not already have a copy of Epi Info™, you can download it from here]
Epi Info™ ─ Mesh4x Synchronization Prototype
View SlideShare presentation or Upload your own. (tags: technology david)

Oswego in the Cloud: Scenario Script
View more documents from Taha Kass-Hout.

During this proof-of-concept, we showed the utility of a Mesh4x tool for synchronizing Epi Info™ data over the cloud (web) and SMS (Please see my previous blog in which I introduced this effort: "Empowering Epidemiologists to Share Information, Anytime, Anywhere: Epi Info™ and Mesh4x"). Epi Info™ is now available as an Open Source project (Please see Official US CDC MMWR release notice and the most recent Government Health IT article: CDC takes its epidemiological software open source).

[The Epi Info™ ─ Mesh4x Synchronization Tool]

[Synchronization over over the Amazon EC2/S3 cloud (State’s available online data in the scenario)]

The Synchronization over SMS using cell phones provides great potential for sharing data among field epidemiologists conducting investigations in areas with limited resources and infrastructure, especially in austere conditions (e.g., during or after disasters).

[Synchronization over SMS]

As part of the scenario, we showed how to share maps across various investigators (in the scenario Oneida county and the neighboring counties). This is especially true as the epidemiologic investigation in underway, that data is shared in aggregate forms; such as a map with a few pins, before further collaboration. During the demonstration, we used Google Earth as the viualization tool to show the various cases (Ill) and no cases are distributed across space (accurately geocodesd) and time (through a time slider). We integrated Google geocoder with the Mesh4x tool to automatically geocode the sample physical addresses and we provided means in the Mesh4x tool to automatically generate and synchronize the maps across the various counties.

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:
  1. Preview/Accept/Reject or "Undo" & Conflict Resolution
  2. Schema/view update and propagation
  3. Mesh-based authentication & authorization
  4. Specify multiple tables to sync
  5. SMS-to-cloud and back
  6. Client to define mesh, feeds, mappings
  7. Privacy & Signatures
[Brainstorming priorities with the Epi Info™ team (from left to right): Roger, Mark and David. Ed facilitated the discussion as you see him going through the projected list]

DISSS is currently seeking a project to continue development of this functionality pending the availability of resources. I'll keep you posted!

We are very grateful for the time and expertise US CDC offered us during this exercise and we wish to further enhance our tools and platform as a result of this effort. I want to personally thank the Epi Info™ team: David Nitschke (lead), Roger Mir and Mark Berndt, and US CDC National Center for Public Health Informatics (or NCPHI) leadership team: Dr. Leslie (Les) Lenert (Director) and Enrique Nieves (DISSS Division Director (Acting)).

[The NCPHI leadership team: Les (left) and Enrique (right)]

I also want to acknowledge my colleagues at InSTEDD who worked really hard over the past six weeks to put this together and to see it succeed, including work done at very early odd morning hours: Juan Marcelo Tondato, Daniel Cazzulino, Pablo M. Cibraro, and Eduardo (Ed) Jezierski.

Finally, on Behalf of InSTEDDers, I want to wish you Happy Holidays and a Happy New Year!

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Friday, December 12, 2008

Empowering Epidemiologists to Share Information, Anytime, Anywhere: Epi Info™ and Mesh4x

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]

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Tuesday, May 20, 2008

A roadmap toward a European healthgrid

This is an exciting work towards building an environment of sharing of resources across heterogeneous and dispersed health data:
Also, an application which can be accessed by all users as a tailored information system according to their level of authorization and without loss of information. Collaboration is the heart of this especially across multiple disciplines. In addition, many standards have not yet been realized (e.g., HL7 (Health Level Seven), the US based Standards Development Organization that currently offers asynchronous messaging), this makes a grid approach far more powerful where organizations join the grid and make their information available for querying, processing, analysis, etc.

Few challenges remain, such as:
  • How do we secure and maintain high performance of such distributed structure of data integration and computing?
  • How do we close the gap between grid standards and health-related standards [some nice work's been done here by Power, et al]?
  • How do we go about next-generation open source ontologies for medical informatics?
  • How do we close the gap between hospital policies, public health policies, etc. and the grid approach?
  • How do we go about consumerism and patient ownership of her or his data?
If anything, I hope this raises more awareness of the grid application in health and public health - much still remains to be answered.

Successes are already underway in the health community, for example:
But also there are lots of lessons which we can learn from the innovative thinking of efforts like the Google Cloud (click here to learn more about cloud computing). In addition, InSTEDD’s Mesh4x allows for asynchronous integration of data between many different sources regardless of network connection, systems or services. Network connectivity is not a constant requirement, as Mesh4x can collect and distribute updates between two users over SMS, Internet (HTTP exchange), or through other available means. InSTEDD recently partnered with the United States Centers for Disease Control and Prevention (CDC) and developed a synchronization adapter for Epi Info™, CDC's application for field collection of disease outbreak information (you can read more about this project in 2 of my previous blogs: Empowering Epidemiologists to Share Information, Anytime, Anywhere: Epi Info™ and Mesh4x, and our final demonstration in December 2008: Epi Info™ and Mesh4x Prototype Demonstration with US CDC).


I'd be very interested to hear your thoughts on this...

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