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It’s time to create a national pandemic forecasting agency

The big idea who could save the world from the next catastrophic pandemic isn’t fully buried in the Biden administration Covid-19 Strategy, but it’s not exactly above the fold, either. After flipping through the executive summary, you will need to scroll a little further down – to page 115 of the 200-page plan – to find it: “To improve the preparedness of the United States, the Administration will endeavor to Obtain congressional funding and support to create a National Integrated Center for Outbreak Forecasting and Outbreak Analysis to modernize global early warning and triggering systems to prevent, detect and respond to biological threats. “

This is it – Federal PreCrime for Pandemics. Precognitive epidemiology. Compose the sci-fi words you want; the point is that one thing the Covid-19 pandemic has proven is that pandemics can and certainly will happen again. Building a place to develop sophisticated models and simulations that can give some idea of ​​when and where an outbreak is, and give advice on how to stop it… well, that sounds like a really good idea.

This notion has been prevalent in Wonk circles since the years after the anthrax attacks of 2001, and it returns with every major epidemic. Two longtime advocates, epidemiologist Caitlin Rivers of the Johns Hopkins Center for Health Security and Dylan George, vice president of the venture capital firm affiliated with intelligence agency In-Q-Tel, introduced it more recently and in more detail in a item in Foreign Affairs. Think of it, they say, as a national weather service, but to predict and study pandemics and epidemics rather than hurricanes and tornadoes. It would combine data collection capabilities with a centralized approach to the kinds of epidemiological and statistical models that featured so heavily in the early months of the Covid-19 pandemic.

America’s climate and weather infrastructure combines data from ocean buoys, barometer and thermometer readings everywhere, and satellite imagery, using predictive engines to generate analysis and simulations on everything. of how climate change is make hurricanes worse where the freighters should go, if you have to carry an umbrella. So similarly, an epidemic analysis center could combine genomic surveillance and public health data with, for example, notes on mosquito and bat populations, to indicate where next epidemics might break out. “We have public health emergencies all the time, even more than people think,” Rivers tells me. Before Covid-19, there was Zika, Ebola, H1N1, H5N1, SARS, anthrax – not to mention seasonal flu, or long-standing global threats like tuberculosis. “These crises give the impression of being continuous, and each time, this capacity for analysis is necessary. But it’s usually only model makers working in academia who volunteer, ”she continues.

This is not a way to run a country in an emergency, especially when the resources to deal with public health crises come from the federal government, but policies and field deployments occur at the levels of state and local. “When you’re trying to incorporate people with a range of different skills or perspectives in the midst of a crisis, who may not have the experience of working at the speed of an epidemic or of working with makers, it’s hard to reconcile that, ”says Rivers. .

To be clear, she is summer say that. About ten years ago, she and George were part of a task force set up at the Office of Science and Technology Policy to study pandemic prediction capabilities. It seemed that one of the problems with the government’s handling of the H1N1 pandemic had been a push-pull in the advice epidemiologists were giving to responders – dueling models. George says that at the time, the Centers for Disease Control and Prevention, the heart of America’s federal public health infrastructure, didn’t really have the capacity to assess which models were the right ones at the right times. And there wasn’t enough permanent capacity to build the best models from scratch. “When a hurricane hits the East Coast, we don’t randomly ask modelers at academic institutions across the United States, ‘Hey, could you drop what you’re doing and model where this hurricane is going to hit?’ There has been this incremental investment in people, models, systems and data to improve forecasting skills, ”he says. “We are in the early stages of forecasting infectious diseases and the pandemic. I am convinced that we can improve a lot if we make a similar investment. “

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