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.