Additionally, Damien said, "Take school closures as an example. It's challenging to assess when and where to close schools. Based on what metric? Percent infected? Percent likely to be infected? Only by using mathematical methods can we best quantify these uncertainties. The MIDAS program rightly encourages the use of mathematics to make better, informed decisions, and we're excited to be involved in such an effort."

Thus, there are many factors that can affect the spread of diseases including population densities, closures of schools and public places, how drugs and vaccines are distributed, cost of treatments and people's perceptions of vaccines.

"Our models will combine these factors and allow us to design public health policies that not only use resources effectively but also influence individual decision making to prevent the transmission of diseases like flu," Meyers said.

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