Just like snow or a storm, the outbreak of diseases can be predicted, according to honorary professor Alessandro Vespignani. The revolution in big data means that we will forecast pandemics much like we predict the weather.
Where should I buy my groceries? In the village down the road, or should I move on to the next town? Alessandro Vespignani, of Northeastern University in Boston, believes that soon we will have an app on our phone telling us what places to avoid to minimise our chances of getting ill. An app will tell you where influenza prevails, for example.
“In only a few years’ time we will see this technology appear,” or so Vespignani said during the seminar Health and Technology, one of the dies celebration seminars held on Thursday January 12, 2017. “Of course this raises a lot of ethical questions.”
Virus expert
Vespignani is an expert in the spread of viruses. He was appointed as one of the four new honorary professors during the dies celebration. He is renowned for his work on Ebola and Zika. In 2001 he combined the two fields in which he was active – statistical physics and network science – to create a new field; network epidemiology.
“This was a marvelous idea,” said network scientist Piet van Mieghem (Faculty of Electrical Engineering, Mathematics and Computer Science), who also gave a lecture. “It set the ground for a lot of work on the modeling of the spread of diseases, worldwide, including here at the TU Delft.”
Weather forecast
The prediction of diseases is lagging behind weather forecasts. Vespignani: “In 1955 the first numerical computer simulations for weather forecast were used. The first equations for epidemics also date from the fifties. But you have to go all the way to 2005 to see the first large-scale agent-based models.”
What is the underlying reason for this difference in pace? “The most important culprit is the fact that we, the people, are part of the equation. Data about society, about our movements and interactions, are scarce. We sent satellites into orbit to gather data for weather forecast, but we didn’t put in the same effort to collect data about ourselves. This is changing now with the revolution in big data.”
Goldmine
“We are obtaining societal information up to the capillary level from all places in the world, due to the mobile phone everyone now has in his pocket, and due to the things we post on Twitter and Facebook. We also get macroscopic data, information on the movements of planes for instance. Every 1.2 years, more human-driven socioeconomic data is produced than during all previous history.”
The data are a goldmine. Vespignani combines socioeconomic data with clinical and epidemical data to create what he calls a ‘synthetic world of 6 billion people’ to run simulations. “In that world we can plant a disease and we can see where it goes. We can add containment measures to the model, vaccination procedures and travel restrictions and see how these factors influence the spread of the disease.”
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