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How to Predict Responses to Disease

By MIT News

January 16, 2015

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Massachusetts Institute of Technology (MIT) researchers have developed a computer model that could provide a way to predict when populations will overreact to a disease outbreak and help public health officials take steps to limit the dangers.

The model makes forecasts based on data collected from hospitals, social media, and other sources.

One way of analyzing human reactions is by studying news reporting on outbreaks, as well as messages posted on social media, and comparing them with data from hospital records about the actual incidence of the disease. In many cases, the reaction to an outbreak can cause more harm than the disease itself.

To study the phenomenon, the researchers examined data from the 2009 spread of H1N1 flu in Mexico and in Hong Kong, and the 2003 spread of SARS in Hong Kong. They found the model could accurately reproduce the population-level behavior that accompanied those outbreaks.

"I hope in the future, if we could predict that these bad social and economic consequences are going to happen that might cost a lot of money and might cost a lot of lives, that people can take measures to counteract these effects," says MIT professor Marta Gonzalez.

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