The Centers for Disease Control and Prevention (CDC) is spending hundreds of millions of dollars to establish a national “public-private” network to sweep up unprecedented amounts of individual and community data and develop artificial intelligence (AI)-driven models to predict disease outbreaks.
That infrastructure will then help local, state and national health officials identify and implement appropriate “control measures” to manage potential disease outbreaks.
As part of this effort, the agency last week announced an estimated $262.5 million in grant funding over the next five years to establish a network of 13 infectious disease forecasting and analytics centers to coordinate this work across the U.S.
The funding provides roughly $20 million each to 11 universities that were actors in COVID-19 modeling and response. The list includes the Johns Hopkins Center for Health Security, which oversaw the Event 201 simulation and the University of North Carolina Gillings School of Public Health, where Ralph Baricinitiated gain-of-function research.
Two of the centers will be private entities — Kaiser Permanente Southern California and a “disaster preparedness organization” called International Responder Systems LLC, whose relevant experience includes running tabletop exercises for weaponized Anthrax outbreaks and helping to manage the Ebola outbreak in West Africa.
Some centers will work with U.S. Department of Defense (DOD) researchers and bioengineering firms to develop new AI and machine-learning-based modeling tools and platforms to track and predict disease outbreaks across the country.
They will also pilot new tracking and prediction tools in adjacent neighborhoods or among specific demographic groups and scale up “successful” pilot projects.
The grantees will form the Outbreak Analytics and Disease Modeling Network (OADM) through cooperative agreements with the CDC, which will be an active partner in the work.
Michael Rectenwald, Ph.D., author of “Google Archipelago: The Digital Gulag and the Simulation of Freedom,” told The Defender:
“What they’re constructing is a panopticon of epic proportions, which will be inescapable in the future and will make for surveillance, not only of people’s behaviors, but also, as they’ve said themselves, of their very thoughts.”
Rectenwald, who is also a presidential candidate for the Libertarian Party, cited the work of Neil Ferguson, the physicist at Imperial College London who, along with his team, created the epidemiological model in early 2020 that predicted the catastrophic global death toll from COVID-19.
Ferguson’s model was used to justify social distancing, masking and lockdowns.
But his predictions — which were criticized at the time by experts such as Oxford epidemiologist Sunetra Gupta, Ph.D. — turned out to be wildly exaggerated in real-world tests.
“I would anticipate further abuses with this CDC modeling network being set up,” Rectenwald said.
A National Weather Service, but for infectious diseases’
The network is spearheaded by the CDC’s new Center for Forecasting and Outbreak Analytics (CFA), set up by the Biden administration to model, predict and control the course of disease outbreaks across the country.
“We think of ourselves like the National Weather Service, but for infectious diseases,” Caitlin Rivers, Ph.D., a Johns Hopkins epidemiologist and associate director for science at CFA told The Washington Post last year when the White House formally launched the initiative.
“Much like our ability to forecast the severity and landfall of hurricanes, this network will enable us to better predict the trajectory of future outbreaks, empowering response leaders with data and information when they need it most,” the CDC said in its funding announcement for the initiative.
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