‘Worst Case’ Scenario for Flu Estimated
Posted by Xeno on May 1, 2009
There will be about 1,700 U.S. cases of the new H1N1 flu, aka “swine flu,” in the next four weeks under a worst-case scenario, according to a research team’s new simulations.
And a second team working independently, about 200 miles away, on exactly the same question came up with a similar forecast.
As of Thursday, there were 109 lab-confirmed U.S. cases of the new influenza, according to the World Health Organization, which earlier this week raised the risk level of the influenza to one stage below pandemic because the virus is being transmitted within at least two countries in one region of the world. A full pandemic – the virus is also being transmitted within a third country in a different region – is considered imminent.
It is not clear, however, how virulent or deadly this flu strain will become. Flu viruses are unpredictable, and while some in history have proven incredibly deadly, many would-be-pandemics turned out to be quite mild. Also, medicine and public health are more sophisticated today, in terms of treatments and educational campaigns, than they were during the nation’s last pandemic flu in 1968, let alone during the Spanish flu of 1918.
Still, researchers are eager to predict what might happen and Dirk Brockmann has identified the hotspots.
California, Texas and Florida will have most of the cases by late May if Brockmann’s large-scale computer simulations are right. His group at Northwestern University came up with the figure of 1,700 cases by late May, and also projected more than 100 cases for the Chicago area.
“Remember – that’s exponential growth, which means slow at the beginning and then very fast,” Brockmann said. “If you run the worst-case scenario for four months, we’re at a very different number.”
Brockmann’s computer clusters can be used to simulate an infectious disease that spreads among 300 million people. The approach was based on human mobility patterns – daily commuting, intermediate trips and long-distance ones – which helps determine how a disease could potentially spread, and he modeled those on data from a dollar-bill tracking project called WheresGeorge.com. You can track people’s movements, to a certain extent, if you know where they spend cash.
“These networks play an important role in the spread of infectious disease,” he said. “So we’re looking at how people travel in the United States and Europe and trying to find a theory behind human traffic. Then we can unravel the structures within these networks and explain them.”