A century ago, Spanish flu swept the globe, a disaster that resulted in the death of tens of millions. Radical advances in healthcare have improved our ability to detect, and hopefully prevent, another infectious disease pandemic like the 1918 event. But the threat remains. Global trade and travel, population growth and other factors have accelerated the speed at which potentially deadly viruses can spread. Now, the use of advanced data analytics is opening a new front in the battle to prevent a similar tragedy from reoccurring.

Analytics have come a long way in a short time. Early attempts to draw insights from data showed promise, but were hampered by critical flaws. Google’s Flu Trends debuted with much fanfare in 2008, promising to usher in an era of “nowcasting” that could track the prevalence of flu based on people’s searches. Following its widely publicized failure to provide accurate predictions in 2013, Flu Trends became the poster child for the shortcomings of big data.

We’ve moved past that, of course. Digital innovation has improved the scope, depth and sophistication of analytics in many ways. A DXC Technology paper, “Preventing Pandemics: The A to Z of digital disruption,” reveals that many new technologies can help spot and contain the flu bug and other pathogens in many ways.

Artificial intelligence (AI), machine learning, robotics, internet of things (IoT) devices and other monitoring devices (including those used by individuals in their day-to-day lives, such as Fitbits and heart monitors), video analytics and geofencing — all play an invaluable role in monitoring, tracking and managing infectious disease to prevent an outbreak.

Companies supplied with data from these new sources are developing products that improve our ability to identify where outbreaks first occur. Sophisticated computer simulation models can also predict the rate of spread, the number of people infected, demands on healthcare resources and mortality. Real-time insights like these enable authorities to contend with a potential epidemic before it becomes a public health and economic threat.

The same information can be used in other ways. Metabiota, a company that specializes in tracking epidemics with data, has developed sophisticated analyses that estimate public fear and behavioral change for different types of contagion. Leisure travelers who learn about a common cold sweeping a region might not feel the need to alter their plans, but news of a Zika outbreak could cause significant disruption. Understanding the public’s reaction to news about the predicted path of a virus enables insurers to offer spot policies to companies in the travel industry that can help them avoid financial ruin from unexpected business interruptions.

Considering how rapidly the field has advanced in just 10 years, the next decade is likely to yield an even greater abundance of improvements. Those developments may at last allow us to consign epidemics to where they belong — the history books.