Incorporating commuter data into disease forecasts may better predict flu within large metro areas like New York City, according to a study published in PLoS Computational Biology.
Researchers built a model to forecast flu within New York City neighborhoods and boroughs, using data on flu cases from 2008 through 2013. They added in something they called “network connectivity”—commuter data, basically.
The commuter data didn’t improve the accuracy of hyper-local, neighborhood-level forecasts. But it did improve predictions at the borough level, compared to models without that sort of commuter flow built in.