At Los Alamos National Lab, Supercomputers Are Optimizing Vaccine Distribution

By Oliver Peckham

December 17, 2020

Los Alamos National Laboratory (LANL), which operates under the purview of the National Nuclear Security Administration (NNSA), is home to a variety of supercomputers that are typically used for nuclear weapon simulations and related tasks. This year, however, LANL has been spending much of its supercomputing time fighting a different national security threat: COVID-19.

Over the course of the year, LANL has pitted its supercomputing prowess against every aspect of the pandemic, from modeling the virus and its spread to investigating various pharmaceuticals that might mitigate or prevent infections. Now, LANL finds itself facing what may be one of the final challenges posed by SARS-CoV-2: optimizing distribution of the new vaccines that may signal the beginning of the end of COVID-19.

The new vaccines from Pfizer and Moderna have been deemed highly effective by the FDA; unfortunately, doses are likely to be limited for some time. As a result, many state governments are struggling to weigh difficult choices – should the most exposed, like frontline workers, be vaccinated first? Or perhaps the most vulnerable, like the elderly and immunocompromised? And after them, who’s next?

LANL was no stranger to this kind of analysis: earlier in the year, the lab had used supercomputer-powered tools like EpiCast to simulate virtual cities populated by individuals with demographic characteristics to model how COVID-19 would spread under different conditions.

“The first thing we looked at was whether it made a difference to prioritize certain populations – such as healthcare workers – or to just distribute the vaccine randomly,” said Sara Del Valle, the LANL computational epidemiologist who is leading the lab’s COVID-19 modeling efforts. “We learned that prioritizing healthcare workers first was more effective in reducing the number of COVID cases and deaths.”

The lab’s modeling results are not merely an academic or aspirational exercise. Throughout the year, state and federal policymakers paid close attention to LANL’s HPC-enabled epidemiological modeling, and the results were directly used to guide policy decisions. The vaccine modeling is no different – in fact, the lab says that the scenarios are being developed in close coordination with local, state and federal officials. This is particularly true of New Mexico, LANL’s home state.

“Our ongoing collaboration with the modeling team at Los Alamos National Laboratory continues as we plan and refine the best ways to distribute the vaccine in a safe, equitable and effective way,” Matt Nerzig, a spokesman for the New Mexico governor’s office, told the Santa Fe Reporter. “From the start of the pandemic, we have made every effort to rely on the best possible data and analysis to fight the virus.”

While the vaccines are extraordinarily promising, the researchers caution that the models show they are not yet a silver bullet for the pandemic – and may not be for some time.

“These models very clearly illustrate that, for many months, the vaccine alone isn’t going to be enough to keep us safe,” said Ben McMahon, a mathematical epidemiologist at LANL. “Given the limited vaccine supply and the fact that immunity builds steadily for several weeks after vaccination, restrictions such as mask wearing, frequent hand washing, and social distancing will still be required for the next several months to slow the spread of the virus and flatten the curve.”

Accordingly, the good news about vaccination comes with a plea.

“Because we don’t see the immediate impact of our actions, it’s hard sometimes to understand that our behaviors make a difference,” McMahon said. “But they make a tremendous difference. By wearing your mask, social distancing, and, when it’s available, getting the vaccine, you can do a lot to protect yourself and others from getting sick.”

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