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What Zika teaches about data driven decision making

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In the same way that analysts use data to predict medal favourites in Rio, health organisations were doing all they could to predict the spread of the Zika virus both during the after the games.


In the lead up to the Olympics, opinions were divided on whether the Games should proceed due to the Zika epidemic. Since the end of May, 240 health experts signed an open letter to the Director-General of the World Health Organisation (WHO) asking for the postponement and/or relocation of the Games.


Highly anticipated golfers, tennis players, cyclists and basketball players withdrew, citing potential health risks to themselves and their families. Many countries took precautions by providing window screens, “Zika-proof” uniforms and insect repellent. Athletes arrived in Rio and took to Twitter, posting images of themselves with mosquito repellent and mosquito nets.


However, at the same time, the WHO published a news release stating that, “cancelling or changing the location of the 2016 Olympics will not significantly alter the international spread of Zika virus.”


So, with wildly different opinions and the social media echo chamber working overtime, what was really going on?


What the science says


Amongst the justified preventative measures and the headline-hype, a few medical and scientific groups were using big data to assess the number of Zika virus transmissions that could result from visiting Rio during the Olympics.


The Centers for Disease Control and Prevention (CDC) conducted a risk analysis to predict those countries at risk for Zika virus spread - attributable to the Games. They assessed each of the 206 countries against 5 criteria, and looked at estimated air travel from Rio de Janeiro during August 2016, as the proportion of each country’s total travel to all Zika-affected countries during 2015.


Analysing these big numbers led to the report stating that the Games do not pose a unique or substantive risk for mosquito-borne transmission of Zika virus in excess of that posed by non-Games travel.”


Researchers from Yale School of Public Health took another tack and calculated the probability for infection. By dividing the total Zika infections in 2015, by the at-risk population, then adjusting for the likely transmission in August - based on the seasonal dynamics of dengue infection they arrived at a similar conclusion.


According to the authors, their model provided a worst-case scenario, assuming that visitors encounter the same infectious exposures as local residents. Under these overly pessimistic conditions, they estimated between 6 and 80 total Zika virus infections among travellers attending the Olympics.


Balancing instinct with analytics


It’s a familiar story to those that work in the field of data analytics, particularly with complex issues like the spread of a disease. Too often “gut feel” or insufficient analysis is used to make decisions that have lasting implications on business.


And while the complexities of analysing big data sets to protect people might seem a mile away from day-to-day New Zealand business, there are some valuable lessons we can take from it.


Ed Hyde, CEO of Qrious, a company that exists to create value for NZ businesses and government through the smart use of data, says, “Many companies are now using data from within their own business to inform decisions. And while this analysis is more scientific than pure instinct, looking outside your immediate surroundings can give you a more complete story to turn into action.”


Ed explains, “For instance, health organisations are correlating weather data with anonymised health information to predict trends in the arrival of diseases such as flu and to spot regional health trends in real-time. That enables them to re-deploy health professionals to areas of high demand, and improve public healthcare services.”


Auckland Tourism, Events and Economic Development (ATEED), engaged Qrious for insight on what was really happening at events. Until that point, ATEED had been relying on pen and paper surveys and crowd counts to plan.


Ed says, “By using public transport numbers, aggregated and anonymised Spark mobile location data and open data sources, we dispelled the myth that the Auckland Lantern Festival was a family event - it’s visited mostly by 18-25 year old urban dwellers. So ATEED changed its mind about moving the event out of the central city, and chose the Auckland Domain to appeal to the largest part of the audience.”


It’s not just public sector organisations that can benefit from big data use and analysis.


The Business Figures website gives businesses of all sizes the ability to find census, industry, employment, population and location data that they can overlay on their own findings for business decision and marketing use.


The marketing arena is a hotspot for big data now because there’s so much information available from digital and social networking platforms. “We’re using transactional, behavioural demographic and social networking data to offer customers compelling marketing advantages and new revenue streams,” says Ed. “Mastering the complexity of data gathering and analysis gives us facts we can trust and uncovers the real story behind the information.”


Want to know more about how Qrious and data discovery can lead to business and marketing advantages? Talk to Qrious today: visit or email



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