Research project will also use financial records to track how the illness spreads.

Health authorities could gain an unprecedented picture of how the flu spreads with complex models that reveal how we move among each other.

New Zealand scientists will combine new DNA data and information gathered from such mass indicators as cellphone location and money transactions to find out how different strains of the flu travel.

The three-year study is among a diverse range of projects to be initiated by a new research institute to be launched in Auckland tomorrow.

The most recent ESR annual data showed influenza-like illnesses affected more than 25,000 Kiwis in the 2013 winter, compared with 48,186 people the year before.

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Of 2326 flu viruses detected at "sentinel" clinics, the vast majority were identified as one of two types, with a mix of less-common strains.

With a comprehensive model that draws on what's called viral phylodynamics, health authorities could have a picture of how these strains of the flu move around and which regions are hot-spots for incubation or priorities for vaccination. The research, led by University of Auckland bioinformatics Professor Alexei Drummond, would draw on a combination of DNA data and indicators of human movement.

New strains of the flu could be spread through Auckland and Christchurch via international travellers and then mutate as they spread throughout the population, while other strains that evolve here could be passed to the rest of the world.

"So we are really interested in trying to track this," said Professor Shaun Hendy, director of Te Punaha Matatini - The Centre for Complex Systems and Networks, which would oversee the work.

"We will be analysing genetic data from the influenza virus, something that is getting cheaper to do, while also trying to look at large-scale population movements through approaches like cellphone location data and financial transaction data.

"More and more people are using apps that record what we are up to, and most of us have smartphones that provide information about the places we go on a daily basis.

"Of course, we don't want to zero in on particular people, because of the privacy concerns, but when you step back and look at data on how New Zealanders interact at a very high level, you will be able to see patterns in what is going on."

Over the last decade, scientists have become increasingly interested in social networks, with the same principles that are used to understand the interaction of atoms now being applied to how humans move among each other each day.

"At the moment, the models we use to track the flu largely assume that everybody has a chance of meeting everyone else - that there's no fine structure in these models of how people actually interact - and so really, we are trying to modify these models so that they can capture that individual-level detail."

ESR virologist Dr Richard Hall said the model would make simple data more valuable.

The model could also be applicable to other contagions - and could help prepare decision-makers for the outbreak of a foreign, high-risk pathogen.

The very same concept could be borrowed when tracking the spread of ideas, Professor Hendy said.

Taking complex mathematical models outside fundamental science to tackle everyday problems would be a large role of the institute - a University of Auckland-based Centre of Research Excellence being formally opened tomorrow.

"This is the right time to be getting involved in this type of study, as it can have a big impact on our daily lives, as well as giving us a broader understanding of the way our world works."

The human equation
*Scientists will use a combination of collected DNA data and information gathered from cellphone locations and financial transactions to build a complex picture of how flu spreads among our population.
*The unprecedented insight, gained by an approach called viral phylodynamics, could allow health authorities to identify "hot spot" regions for flu incubation and launch targeted immunisation campaigns.
*Advanced mathematical principles which have been typically used to observe the interaction of atoms is now being applied to human interaction, allowing scientists to track even the flow of ideas.