Steve Bennett, SAS’s director of government practice, attributes the dramatic improvement of the medical community’s ability to track and contain infectious outbreaks to the massive improvement of quickly deploy-able data analytics tools.
“Speed is everything. Speed saves lives,” says Bennett.
But if these insights aren’t being applied to public health policy, it’s all just a “science project”, Bennett says.
Buckley Smith filed this report for IT World Canada:
Almost 20 years ago now, SARS infected 8,090 people, of which 774 died, according to stats from the CDC. Bennett said that he has seen two major advancements in the analytics field since then.
The first of those advancements being the development of AI and machine learning, which Bennett said has had great effects in speeding up the development of vaccines when applied to data about past diseases to find genetic similarities.
What in the past took up to 10 years, now takes only about 18 to 24 months. And in fact, just last year, scientists in Australia unveiled the first AI-developed vaccine in the world. “It really speeds a lot of things up. We can make better sense of much larger pools of data and get better insights from them much faster than we could previously,” he said. “But it’s still not good enough. We want to use this technology to make things go even faster.”
The second major advancement that Bennett noted was not a technological advancement at all but was instead the popularization of the practise of sharing data. “One of the biggest things that we’ve seen since 2003 is more openness among other countries and health organizations in sharing data. If you don’t have the data… or it’s old or it’s incomplete, you’re really starting blind,” he explained. “We’re seeing better openness about sharing information. The quicker you can get information shared globally, the more quickly the best minds and the best analysts can start to work on it. And it really does save lives.”
But all of this is for naught, said Bennett, if the insights gained from these analytic tools are not turned into actions on the ground, not only in preventing current pandemics but also in preparing for future ones. “We can do all the data analysis we want, but if it doesn’t really help somebody take better public health or policy action, none of it matters. It’s just a science project,” explained Bennett.