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VBI Uses Synthetic Population to Study City Epidemic Spread

Thursday, January 23, 2014  
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Researchers in the Network Dynamics and Simulation Science Laboratory at the Virginia Bioinformatics Institute are the first to model in detail how transient populations impact the spread of an illness, and how outbreaks such as influenza can be curbed by encouraging healthy behaviors in high-traffic tourist destinations.

In a large city like Washington, D.C., with about 50,000 visitors on any given day who stay for just a few days, there is a constant influx of new people who are susceptible to infections. Further, they visit highly populated tourist destinations, where they come into contact with other visitors as well as residents. Disease can spread quickly.

"We built a detailed synthetic population model of Washington, D.C., including transient populations: tourists, business travelers," said Samarth Swarup, an applied computer scientist at the institute. "Our computational model shows that an influenza epidemic can be much worse when we take the impact of transients into account.”

The simulations determined whether closing the area’s main museums for varying durations would affect the spread of the illness, and also whether the spread of the illness was slowed if healthy behaviors, such as covering coughs and using hand sanitizers, were encouraged at these main tourist destinations.

They also analyzed the spread of the epidemic and derived the average number of contacts per day, per individual, and the average duration per contact.

Their studies revealed that by encouraging healthy behaviors at locations of high mixing, such as the museums of the Smithsonian Institution, the outbreak size could be significantly reduced, and the peak of the epidemic could be significantly reduced and delayed. It turns out that this is much better than simply closing the museums for a few days a kind of "social distancing" intervention, which seems to have no effect on the epidemic.

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