Source: ChildrensHealthDefense.org
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 Baric initiated 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.
Others will work with insurance companies, healthcare providers, local health departments and others to collect data from people’s search histories, personal communications, social media posts, wastewater, health records and more.
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.”
He said the COVID-19 pandemic response provided a paradigmatic example of the dangers of predictive modeling.
“The use of modeling is a very poor predictor of infectious disease, and it has been abused in the past, in particular with reference to COVID-19.”
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.
Just as the weather forecast helps people to decide whether to take an umbrella with them when it predicts rain, for example, a disease forecast can help people decide if they should bring a mask, or have a birthday party inside or outside, Rivers told the Post.
In July, Eric Rescorla, former chief technology officer at Mozilla who was tapped to be chief technologist for CFA, told Politico it is “a startup in government” that will need a lot of government funding and that will work very closely with private industry.
The surveillance ‘the American people want and deserve’?
CFA was formally established as part of the CDC in January of this year, but it has been in the works at least since January 2021, when Biden announced plans for the agency in the administration’s first national security memorandum.
CFA received its first $200 million in August 2021 from the American Rescue Plan Act.
Then-CDC Director Rochelle Walensky, who consistently pushed for legislative and other changes to “modernize the public health data policy framework” when she was in office, said at the time:
“This new center is an example of how we are modernizing the ways we prepare for and respond to public health threats. I am proud of the work that has come out of this group thus far and eager to see continued innovation in the use of data, modeling, and analytics to improve outbreak responses.”
CFA began making grants in Oct. 2021, awarding $21 million to five academic institutions — including Johns Hopkins and Harvard — and $5 million to the National Science Foundation and the Department of Energy to develop disease modeling capabilities.
CFA worked with academic partners to model, predict and “warn” the government of the omicron spread from November to December 2021.
In December 2022, the CDC renewed its partnership with Peter Theil’s CIA-linked data mining firm Palantir, signing a $443 million contract “to employ scalable technology to plan, manage, and respond to future outbreaks and public health incidents” — an award meant, in part, to “help support innovation” for CFA.
Earlier this year a GOP House subcommittee tried to cut funding to the center, but CDC Director Mandy Cohen told STAT News she was fighting for the funding. She said:
“Folks want us to be ready to know of threats and to respond quickly. Well, we need data and visibility to do that. And so that is money that will help us to see threats and respond to threats faster. And that’s what I think the American people want and deserve.”
But Rectenwald warned that rather than protecting people this system will be a threat to anyone who doesn’t comply with coercive public health directives. He said:
“The surveillance that they’re unrolling here has great potential for infringement on privacy and also for targeting individuals and groups for non-compliance, and as such, abuses of their civil rights and liberties.
“This system will be capable of locating individuals and communities that are not abiding by the coercive measures being ‘recommended.’ And then they can impose even harsher restrictions on these same people. So this is a very, very pernicious prospect.”
CFA reveals ‘a revolving door’ between biotech, government health agencies and the DOD
Rectenwald told The Defender that the CFA collaboration reveals a revolving door phenomenon that we see in government more generally.
“We have government officials being drawn from the private sector and then granting awards that go back to the companies for which they worked, or to which they’re headed. There’s a lot of collusion underway here,” he said.
CFA is headed by Dylan George, Ph.D., who has spent his career moving between U.S. government health agencies, and the DOD and just prior to being tapped to head up CFA, he had a five-month stint at biotech firm Ginko Bioworks.
Ginkgo Bioworks is one of the only private firms explicitly named as a partner on one of the CFA grant awards, with Northeastern University. It is also a key partner in developing other global pandemic surveillance and predictive programs, such as the Rockefeller Foundation’s Pandemic Prevention Institute.
Besides Ginko and Palantir, CFA’s website indicates it partners with “many” public and private organizations. In April 2022, CFA convened a conference called “CFA: 101 for Industry.”
At the conference, George, along with representatives from Databricks, Peraton, Microsoft, RTI, Dell Technologies Redhat/Carahsoft, Optum Serve and Maximus Public Health Analytics, gave presentations on the importance of “public-private partnerships” to CFA’s work.
The industry representatives also discussed their current and past collaborations with CDC to develop the tracking and analytic tools and platforms CFA hopes to ramp up.
Panelists included Michelle Holko — formerly of DARPA (Defense Advanced Research Projects Agency), principal architect scientist at Google Cloud for healthcare and life sciences at the time of the conference in 2022, and currently chief strategist for Defensive BioTech — who spoke on the origins of CFA’s disease forecast research in DARPA.
Holko, also a former fellow at the National Institutes of Health (NIH) and Johns Hopkins Center for Biosecurity, talked about the value of Google search histories and personal digital interaction data to affect public health outcomes.
They provide key information, she said, “because, you know, a person’s desire and willingness to get vaccinated has a huge impact on what’s to happen with a public health crisis,” she said.
‘A new age of public health’: example data collection, prediction and control projects
Data can be used to understand people’s desire, but also “everything that’s going on in their environment, and in their thoughts and in their circle,” Holko said, which has serious implications for public health.
To illustrate how such data could be used, she explained how Google collaborated with the state of California during the COVID-19 pandemic to mine people’s search data and other personal data. They developed a “vaccine willingness score” for each individual person whose data they analyzed.
Then they positioned mobile vaccine vans in neighborhoods with low vaccine rates but some willingness to be vaccinated.
“They were able to take a 25% gap between the lowest quartiles of the Healthy Places index and the highest quartiles and just flip that right upside down,” she said, adding that such targeting addresses a health equity issue.
Holko also talked about the value of wearables in capturing biological data, which, she said, might make it possible to detect a pathogen inside of a person’s body even if they aren’t experiencing symptoms.
Rivers added that it would be important for public health agencies like CFA to get the things they need — like the ability to go out and swab anyone whose data they need directly — rather than having to depend on other adjacent data sources like biometric data, social media data, etc.
Researchers at RTI presented their RTI Synthetic Population project where they have modeled a “synthetic population” of over 300 million individuals, each representing a U.S. person, with their attributes, age, race gender, income, education attainment, job and whatever other data they can glean, which they then use to project epidemiological events.
There were many such presentations.
The overall takeaway was that the contemporary availability of massive amounts of data has created a “new age of public health” and a mandate for new tools to capture and analyze data using novel applications of machine learning and artificial intelligence.
George said many of the people in the room had been dreaming of a forecasting network like CFA for almost a decade, and they had been “right to be opportunistic” about the “window of opportunity” that presented itself for them to finally set it up.
The ‘extremely ironic’ list of grantees
The OADM is the first major initiative by CFA and sets up its infrastructure across the country. The 13 centers in the network will act as networks themselves.
As the CDC put it:
“In the aftermath of the COVID-19 pandemic, CDC has worked collaboratively with state, local, tribal, and territorial health departments, public health organizations, academia, and the private sector to improve and scale outbreak response and provide support to leaders to prevent infections and save lives.
“This national network will build on these collaborations and improve outbreak response using data, modeling, and advanced analytics for ongoing and future infectious disease threats and public health emergencies.”
Awardees include:
- Johns Hopkins Center for Health Security received $23.5 million for its project, “Toward Epidemic Preparedness: Enhancing Public Health Infrastructure and Incorporating Data-Driven Tools.” It will create partnerships with “public health stakeholders” and it will train students, practitioners and modelers — including meteorologists — to use modeling and analytic tools.
- The University of North Carolina Gillings School of Public Health was awarded $22.5 million to support the creation of the Atlantic Coast Center for Infectious Disease Dynamics and Analytics, which will develop methods, tools and platforms for disease modeling and coordinate them among the 13 funded partners in the network.
- Northeastern University won $17.5 million for an “innovation center” called “Epistorm: The Center for Advanced Epidemic Analytics and Predictive Modeling Technology.” Epistorm will coordinate efforts among ten healthcare systems, research organizations and private companies to use data from wastewater surveillance, social media, and hospital admissions and apply AI and machine learning tools and other predictive analytics. The consortium’s academic members include Boston University, Indiana University, the University of Florida and the University of California at San Diego. Other members include Los Alamos National Laboratory (LANL), the Fred Hutchinson Cancer Center, MaineHealth, Northern Light Health and Concentric Ginkgo Bioworks.
- The University of California at San Diego (UCSD) won $17.5 million to “develop innovative tools and networks” that analyze data sources to determine their predictive power. Data sources will include molecular epidemiological data, wastewater and air surveillance; exposure notification systems (smartphones and contact tracing), internet searches and posts, “legally available clinical data,” and scenario-based simulations. The team will pilot test their innovations among vulnerable populations in San Diego, including homeless people and drug users. UCSD will also partner with other California universities and LANL.
- A team of researchers at the University of Texas at Austin and University of Massachusetts Amherst was awarded $27.5 million to scale up decision-support tools that have been used in previous outbreaks. They will partner with two dozen other entities, including local public health agencies. Northwestern University received $1.7 million in funding to support these efforts.
- Carnegie Mellon University will receive $17.5 million to expand on work it did during the COVID-19 pandemic, gathering daily data “from health care systems, technology companies, medical test results, insurance claims and surveys” to steer policy and public health decisions by applying machine learning and AI tools. It will work with public health agencies and with healthcare providers like Optum to make healthcare data available to researchers.
- The University of Michigan School of Public Health won approximately $17.5 million to establish the Michigan Public Health Integrated Center for Outbreak Analytics and Modeling, which will develop modeling and data analytics tools and pipelines to be integrated into the Michigan Department of Health and Human Services systems.
- The University of Minnesota School of Public Health and the Minnesota Department of Public Health (MDH) will receive $17.5 million to develop predictive tools by surveying individual community interactions and developing machine-learning algorithms to identify symptom clusters. They will work closely with the Minnesota Electronic Health Record Consortium, a partnership between the MDH and the 11 largest health systems in the state.
- A team of researchers at Emory University will receive $17.5 million to “innovate” new analytical methods, tools and platforms to inform public health decisions.
- Clemson University will work with the University of South Carolina, Medical University of South Carolina, Prisma Health, South Carolina Department of Health and Environmental Control, Clemson Rural Health, and South Carolina Center for Rural and Primary Health Care to integrate forecasting and decision-making tools.
- The University of Utah received $17.5 million for its new ForeSITE (Forecasting and Surveillance of Infectious Threats and Epidemics) center, which will “provide data and tools” to guide decisions about emerging public health threats. It will do this through partnerships with the national Veterans Affairs health system and hospitals and health departments in Utah, Washington, Idaho and Montana.
- Kaiser Permanente Southern California will work in partnership with academic modeling teams based at the University of California, Berkeley, and the University of California, San Francisco, using its 4.7 million members as a basis to “develop and test strategies to improve use of public health data.”
- International Responder Systems will work with the University of California, Los Angeles, and Primary Diagnostics “to deliver an enhanced outbreak analytics diagnostic system and a continuous education program to upskill our public health workforce.
Rectenwald said:
“It’s extremely ironic that these universities and institutions have been chosen to undertake the research and modeling. For example, the University of North Carolina Gilling School of Global Public Health initiated gain-of-function research, which was then undertaken in Wuhan, but funded by the NIH through EcoHealth Alliance.
“So isn’t it ironic that this school, the university research center that had a great deal to do with the gain-of-function research that led to COVID-19, is now getting 4.5 million annually for five years?
“It’s an outrage.
“And the Johns Hopkins Center for Health Security is receiving $23.5 million from the CFA to conduct its project. Curiously, the same center was also the host and organizer of two major events, the CLADE X simulation and the Event 201 simulation, both of which forecasted, in advance of COVID-19, almost the exact scenario that unfolded.
“I wouldn’t trust that Center for Health Security at Johns Hopkins with this kind of money and this kind of power to direct the behavior of governments, health organizations, localities, and states in response to anything because they forecasted the kinds of draconian lockdowns, masking, and forced vaccinations that took place in response to COVID-19.
“Likewise, in this scenario, I would expect them to advocate the exact same kinds of measures.”