Instrumented Interconnecteds Intelligent

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Smarter Planet stories are everywhere. We just have to look and listen for them. Take my recent family vacation to Toronto, to visit my sister-in-law Amy Khan, her husband Kamran Khan and their three adorable children Lotus, Ozzie and Darwin.

Over the course of the vacation, I had numerous conversations with Kamran about his primary project, Bio.Diaspora, and how it seems like the perfect example of a Smarter Planet project. In all these conversations, Khan spoke with the modesty typical in his native city of Toronto. But the more I spoke with him, the more I realized that this modesty belies the substance of his work, which recently won honors from ComputerWorld.

Khan runs Bio.Diaspora, a project based at St. Michael’s Hospital–a teaching hospital affiliated with the University of Toronto–which builds data models to help large organizations anticipate and mitigate the risks of global infectious disease threats.

Khan has and continues to partner with large public health agencies including the U.S. Centers for Disease Control and Prevention (CDC), the Public Health Agency of Canada, the European Centre for Disease Prevention and Control, and the World Health Organization to name a few. More recently, national defense and biosecurity organizations, and even large multinational corporations whose activities are impacted by infectious disease epidemics or pandemics have expressed interest.


One such organization is the set of public health partners preparing for the for the 2012 Summer Olympics Games in London. If an athlete, a spectator, a local resident, or a visitor who happens to be traveling in London during the Games introduces a dangerous infectious disease that can easily be spread to others, then the city could become an epidemic hot zone. All the more dangerous, individuals who are locally exposed to the disease, could then introduce it into their home countries after the Games are over.

My family and I spent a delightful Canada Day on the Toronto Islands with Khan and his family. As we took the ferry from the islands back to the city, the magnitude of the 2012 Olympic challenge hit home for me. As hundreds of people from the world’s most ethnically diverse city crowded onto the boat, I contemplated the possibility that one of them might be carrying a dangerous virus.

Khan, who was standing next to me, must have read my mind. “Each one of these people has come in contact with hundreds if not thousands of other people over the last week,” he said. “And many of these person-to-person contacts have occurred in cities and countries all around the world. Now multiply the scale of what is happening on this ferry by a hundred thousand. That is the challenge faced during mass gatherings like the Olympics.”

How Bio.Diaspora works

The models are based on the fact that the rules that govern how infectious diseases rapidly spread worldwide are largely the same rules that govern how we travel around the globe on commercial flights. Khan feeds data he acquires from worldwide airline ticket sales, airport statistics from thousands of airports, global flight schedules and a plethora of other complementary sources into his model to predict how infectious diseases such as pandemic H1N1 are likely to spread around the world.

His team’s model accurately predicted how the novel H1N1 influenza virus, emerging in Mexico, would spread worldwide. For the first time, this work validated the notion that knowledge of global travel patterns could be used to anticipate how infectious diseases are likely spread, and consequently could be used to intelligently prepare for infectious disease threats before they occur. Many thought the 2009 H1N1 outbreak might rival the Spanish Flu, which killed an estimated 50 million people between 1918 and 1920 (before commercial air travel existed). The CDC estimates that the death toll from the 2009 H1N1 outbreak was less than 18,000.

Flightlines tracked by Boi.Diaspora

Flightlines tracked by Boi.Diaspora

Khan primarily works out of his Toronto lab, but collaborates with colleagues from all around the globe. One of his closest collaborators is John Brownstein, a Harvard professor whose work in a project called HealthMap focuses on producing global epidemic intelligence by mining data from the Internet to detect infectious disease outbreaks at their earliest stages. Brownstein accomplishes this by scraping online text around the clock from tens of thousands of websites published in nine different languages. Using a combination of automated and manual filtration methods, background noise is then separated from signals of potentially dangerous infectious disease events. Brownstein’s also harnesses information from social media to look for spikes in infectious disease related chatter that could signal the onset of an emerging threat.

Khan feeds these and other data into his models to help predict the spread of these outbreaks, such as the recent E. coli O104 epidemic emerging in Germany. He then sends analyses he and his team rapidly generate to his national and international partners–typically organizations that directly respond to the threat of imported infectious diseases and who require real-time intelligence to make sound, evidence-based decisions to protect public health security from infectious diseases. His list of partners is rapidly growing, and now includes organizations that operate mass gatherings, such as the annual Hajj pilgrimage in Mecca, Saudi Arabia and the Olympic Games.

The risks and benefits of mass gatherings

Humans are social creatures who congregate for a plethora of different reasons. Now imagine millions of people from all over the world converging on a single city and mingling in dense, crowded environments for weeks on end. Now imagine that city has the highest volume of international air traffic of any in the world, and that the convergence of populations is scheduled to occur during the midst of its peak travel season. This is the challenge facing public health planners for the 2012 Summer Olympics Games in London.

Recognizing the challenge, Khan and Brownstein are partnering with the National Health Service in the United Kingdom, to model how the world is expected to converge on London, England next July and concurrently “listen for Internet chatter” of possible infectious disease threats leading up to, during, and shortly after the Games. This epidemic intelligence will provide public health officials in the United Kingdom with around the clock situational awareness of global infectious disease events that, if needed, could help mobilize strategic public health countermeasures.

Global interconnectedness and interdependence

The good news is that organizers of the Olympics have diligently been working with public health officials in the United Kingdom well in advance of the Games to ensure that they are prepared to deal with any health threat. Thanks to Khan, Brownstein and their respective systems, these health officials will have access to around the clock news of potential infectious disease threats in the world and an understanding of if and how these threats might find their way into London during the Games. Their systems are instrumented to use social media, community based reporting via cell phones and official public health reports. Their systems model the interconnectedness of how diseases spread like spores blowing around the globe. Their systems use intelligence to analyze this data with predictive modeling. The combination creates smarter prevention and response to infectious diseases.

“The world is increasingly interconnected and this offers humanity amazing benefits,” Khan said. “But interconnectedness is also deeply intertwined with interdependence, whether economic in nature or related to infectious diseases. And we know that infectious diseases pose health and security risks and are enormously disruptive to local and global economic activity. Bio.Diaspora is dedicated to maximizing the benefits of living in an interconnected world while concurrently minimizing its risks.”

James Mathewson is the global search strategy lead for IBM digital marketing and author of Audience, Relevance and Search: Targeting Web Audiences with Relevant Content.”

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September 19, 2011
3:48 am

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