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September 02, 2005

[no title]

To Model or Not to Model ... THAT is the Question!

Janine Burbage, IBM Healthcare & Life Sciences, Business Development

There isn't a day that goes by that I don't get at least 36 Google alerts on "avian flu", "pandemic", or "bird flu". Finding out how IBM services and solutions could help prevent such pandemics is part my responsibilities. I'll be blogging on this and other important public health issues in the months ahead. But incase your summer vaca left you a little behind on the subject of pandemics, let me give you the low down…

It has been 36 years since our last pandemic, (the last one was the Hong Kong Flu in 1968-1969) and many scientists believe that it’s only a matter of time until the next one occurs. Its severity cannot be precisely predicted, but modeling studies show that the effect in the United States could be severe: potentially affecting 66M Americans, hospitalizing two million people in the U.S. alone, and causing over 500,000 deaths. With a little over 965,000 staffed hospital beds in registered American hospitals, imagine how stressed and overwhelmed the U.S. healthcare system would be! The economic impact could be between $71.3 billion and $166.5 billion due to death and lost productivity, excluding other disruptions to commerce and society.

So how likely is it that the Avian Influenza will be the next pandemic? No one knows. The Avian Influenza (H5N1) was first identified in 1961 in South Africa, but it mainly affected birds and animals. H5N1 is zoonotic which means it is capable of jumping from animals to humans. The real danger is if the virus mutates to become contagious from person to person. In 1997, the Avian Flu emerged in Hong Kong killing 6 out of 18 infected. The outbreak was halted until 2003. As of August 5, 2005, the WHO has reported 112 confirmed cases with 57 deaths. The Avian Flu has made its way to Russia, and a few "unconfirmed" cases are being reported in Finland.

Let's talk a little bit about modeling... modeling tools and techniques that not only predict how and where the disease will spread, but will also quantitatively evaluate different response strategies. IBM doesn’t develop epidemiological models per se, but we have the expertise in building modeling frameworks for the kinds of activities mentioned above. For example, IBM Research has developed Spatial-Temporal Epidemiological Modeler, a public health forecasting tool that aids policy makers and planners in evaluating appropriate response strategies to natural or biologic threat of emerging infectious diseases.

But how useful are models? Some skeptics of modeling feel that regardless of how much modeling one performs, the results are only as good as the data used to run the model. Point taken. So I ask you, how do we improve modeling and simulation technologies so that they become trusted and valuable tools for the advisors and decision makers in state, local, and national governments and public health departments?

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Posted by dymaxion at September 2, 2005 01:26 PM

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