Can our technological connectedness trump the risks of our biological and geographic connectedness? That’s one reason Nathan Wolfe has pushed GVF (Globe Viral Forecasting) to pioneer what he calls digital epidemiology, which uses the resources of the Internet to make predictive sense of the viral chatter picked up in the field. He and his team are setting up a bioinformatics strategy that could mine data from Internet searches and social media to pinpoint new outbreaks as they dawn – and potentially predict which newly discovered viruses might pose real threats to humanity. That work is culminating in a project called Epidemic IQ that will, Wolfe hopes, provide the ability to predict new pandemics the way the CIA might predict a terrorist attack.
Current global disease control efforts focus largely on attempting to stop pandemics after they have already emerged. This fire brigade approach, which generally involves drugs, vaccines, and behavioral change, has severe limitations. Just as we discovered in the 1960s that it is better to prevent heart attacks than try to treat them, we realize that it’s better to stop pandemics before they spread and that effort should increasingly be focused on viral forecasting and pandemic prevention.
“We’re finally beginning to understand why pandemics happen instead of just reacting to them”, Wolfe says. What’s needed is a global effort to scale up that kind of proactive work to ensure that every hot spot has surveillance running for new pathogens in animals and in human beings and that it has its own GVF-type group to do the work. Viruses don’t respect borders – whether between nations or between species – and in a world where airlines act like bloodlines, global health is only as strong as its weakest link. We got lucky with the relatively weak swine-flu pandemic in 2009, but history tells us our luck won’t last. “We sit here dodging bullets left and right, assuming we have an invisible shield”, says Wolfe. “But you can’t dodge bullets forever.”
WALSH, Bryan.Virus hunter. Disponível em: <content.time.com/time/subscriber/l>. Acesso em: mai. 2018. Adaptado.
