Posted on by Lawrence Tabak, D.D.S., Ph.D.
It’s good for our health to eat right, exercise, and get plenty of rest. Still, many other things contribute to our sense of wellbeing, including making it a point to practice gratitude whenever we can. With this in mind, I can’t think of a better time than Thanksgiving to recognize just a few of the many reasons that I—and everyone who believes in the mission of the National Institutes of Health (NIH)—have to be grateful.
First, I’m thankful for the many enormously talented people with whom I’ve worked over the past year while performing the duties of the NIH Director. Particular thanks go to those on my immediate team within the Office of the Director. I could not have taken on this challenge without their dedicated support.
I’m also gratified by the continued enthusiasm and support for biomedical research from so many different corners of our society. This includes the many thousands of unsung, patient partners who put their time, effort, and, in some cases, even their lives on the line for the sake of medical progress and promising treatment advances. Without them, clinical research—including the most pivotal clinical trials—simply wouldn’t be possible.
I am most appreciative of the continuing efforts at NIH and across the broader biomedical community to further enable diversity, equity, inclusion, and accessibility within the biomedical research workforce and in all the work that NIH supports.
High on my Thanksgiving list is the widespread availability of COVID-19 bivalent booster shots. These boosters not only guard against older strains of the coronavirus, but also broaden immunity to the newer Omicron variant and its many subvariants. I’m also tremendously grateful for everyone who has—or soon will—get boosted to protect yourself, your loved ones, and your communities as the winter months fast approach.
Another big “thank you” goes out to all the researchers studying Long COVID, the complex and potentially debilitating constellation of symptoms that strikes some people after recovery from COVID-19. I look forward to more answers as this work continues and we certainly couldn’t do it without our patient partners.
I’d also like to express my appreciation for the NIH’s institute and center directors who’ve contributed to the NIH Director’s Blog to showcase NIH’s broad and diverse portfolio of promising research.
Finally, a special thanks to all of you who read this blog. As you gather with family and friends to celebrate this Thanksgiving holiday, I hope the time you spend here gives you a few more reasons to feel grateful and appreciate the importance of NIH in turning scientific discovery into better health for all.
Posted on by Lawrence Tabak, D.D.S., Ph.D.
As colder temperatures settle in and people spend more time gathered indoors, cases of COVID-19 and other respiratory illnesses almost certainly will rise. That’s why, along with scheduling your annual flu shot, it’s now recommended that those age 5 and up should get an updated COVID-19 booster shot [1,2]. Not only will these new boosters guard against the original strain of the coronavirus that started the pandemic, they will heighten your immunity to the Omicron variant and several of the subvariants that continue to circulate in the U.S. with devastating effects.
At last count, about 14.8 million people in the U.S.—including me—have rolled up their sleeves to receive an updated booster shot . It’s a good start, but it also means that most Americans aren’t fully up to date on their COVID-19 vaccines. If you or your loved ones are among them, a new study may provide some needed encouragement to make an appointment at a nearby pharmacy or clinic to get boosted .
A team of NIH-supported researchers found a remarkably low incidence of severe COVID-19 illness last fall, winter, and spring among more than 1.6 million veterans who’d been vaccinated and boosted. Severe illness was also quite low in individuals without immune-compromising conditions.
These latest findings, published in the journal JAMA, come from a research group led by Dan Kelly, University of California, San Francisco. He and his team conducted their study drawing on existing health data from the Veterans Health Administration (VA) within a time window of July 2021 and May 2022.
They identified 1.6 million people who’d had a primary-care visit within the last two years and were fully vaccinated for COVID-19, which included receiving a booster shot. Almost three-quarters of those identified were 65 and older. Nearly all were male, and more than 70 percent had another pre-existing health condition that put them at greater risk of becoming seriously ill from a COVID-19 infection.
Over a 24-week follow-up period for each fully vaccinated individual, 125 per 10,000 people had a breakthrough infection. That’s about 1 percent. Just 8.9 in 10,000 fully vaccinated people—less than 0.1 percent—died or were hospitalized from COVID-19 pneumonia. Drilling down deeper into the data:
• Individuals with an immune-compromising condition had a very low rate of hospitalization or death. In this group, 39.6 per 10,000 people had a serious breakthrough infection. That translates to 0.3 percent.
• For people with other preexisting health conditions, including diabetes and heart disease, hospitalization or death totaled 0.07 percent, or 6.7 per 10,000 people.
• For otherwise healthy adults aged 65 and older, the incidence of hospitalization or death was 1.9 per 10,000 people, or 0.02 percent.
• For boosted participants 65 or younger with no high-risk conditions, hospitalization or death came to less than 1 per 10,000 people. That comes to less than 0.01 percent.
It’s worth noting that these results reflect a period when the Delta and Omicron variants were circulating, and available boosters still were based solely on the original variant. Heading into this winter, the hope is that the updated “bivalent” boosters from Pfizer and Moderna will offer even broader protection as this terrible virus continues to evolve.
The Centers for Disease Control and Prevention continues to recommend that everyone stay up to date with their COVID-19 vaccines. That means all adults and kids 5 and older are encouraged to get boosted if it has been at least two months since their last COVID-19 vaccine dose. For older people and those with other health conditions, it’s even more important given their elevated risk for severe illness.
What if you’ve had a COVID-19 infection recently? Getting vaccinated or boosted a few months after you’ve had a COVID-19 infection will offer you even better protection in the future.
So, if you are among the millions of Americans who’ve been vaccinated for COVID-19 but are now due for a booster, don’t delay. Get yourself boosted to protect your own health and the health of your loved ones as the holidays approach.
 CDC recommends the first updated COVID-19 booster. Centers for Disease Control and Prevention. September 1, 2022.
 CDC expands updated COVID-19 vaccines to include children ages 5 through 11. Centers for Disease Control and Prevention, October 12, 2022.
 COVID-19 vaccinations in the United States. Centers for Disease Control and Prevention.
 Incidence of severe COVID-19 illness following vaccination and booster with BNT162b2, mRNA-1273, and Ad26.COV2.S vaccines. Kelly JD, Leonard S, Hoggatt KJ, Boscardin WJ, Lum EN, Moss-Vazquez TA, Andino R, Wong JK, Byers A, Bravata DM, Tien PC, Keyhani S. JAMA. 2022 Oct 11;328(14):1427-1437.
COVID-19 Research (NIH)
Dan Kelly (University of California, San Francisco)
NIH Support: National Institute of Allergy and Infectious Diseases
Posted on by Lawrence Tabak, D.D.S., Ph.D.
The COVID-19 pandemic continues to present considerable public health challenges in the United States and around the globe. One of the most puzzling is why many people who get over an initial and often relatively mild COVID illness later develop new and potentially debilitating symptoms. These symptoms run the gamut including fatigue, shortness of breath, brain fog, anxiety, and gastrointestinal trouble.
People understandably want answers to help them manage this complex condition referred to as Long COVID syndrome. But because Long COVID is so variable from person to person, it’s extremely difficult to work backwards and determine what these people had in common that might have made them susceptible to Long COVID. The variability also makes it difficult to identify all those who have Long COVID, whether they realize it or not. But a recent study, published in the journal Lancet Digital Health, shows that a well-trained computer and its artificial intelligence can help.
Researchers found that computers, after scanning thousands of electronic health records (EHRs) from people with Long COVID, could reliably make the call. The results, though still preliminary and in need of further validation, point the way to developing a fast, easy-to-use computer algorithm to help determine whether a person with a positive COVID test is likely to battle Long COVID.
In this groundbreaking study, NIH-supported researchers led by Emily Pfaff, University of North Carolina, Chapel Hill, and Melissa Haendel, the University of Colorado Anschutz Medical Campus, Aurora, relied on machine learning. In machine learning, a computer sifts through vast amounts of data to look for patterns. One reason machine learning is so powerful is that it doesn’t require humans to tell the computer which features it should look for. As such, machine learning can pick up on subtle patterns that people would otherwise miss.
In this case, Pfaff, Haendel, and team decided to “train” their computer on EHRs from people who had reported a COVID-19 infection. (The records are de-identified to protect patient privacy.) The researchers found just what they needed in the National COVID Cohort Collaborative (N3C), a national, publicly available data resource sponsored by NIH’s National Center for Advancing Translational Sciences. It is part of NIH’s Researching COVID to Enhance Recovery (RECOVER) initiative, which aims to improve understanding of Long COVID.
The researchers defined a group of more than 1.5 million adults in N3C who either had been diagnosed with COVID-19 or had a record of a positive COVID-19 test at least 90 days prior. Next, they examined common features, including any doctor visits, diagnoses, or medications, from the group’s roughly 100,000 adults.
They fed that EHR data into a computer, along with health information from almost 600 patients who’d been seen at a Long COVID clinic. They developed three machine learning models: one to identify potential long COVID patients across the whole dataset and two others that focused separately on people who had or hadn’t been hospitalized.
All three models proved effective for identifying people with potential Long-COVID. Each of the models had an 85 percent or better discrimination threshold, indicating they are highly accurate. That’s important because, once researchers can identify those with Long COVID in a large database of people such as N3C, they can begin to ask and answer many critical questions about any differences in an individual’s risk factors or treatment that might explain why some get Long COVID and others don’t.
This new study is also an excellent example of N3C’s goal to assemble data from EHRs that enable researchers around the world to get rapid answers and seek effective interventions for COVID-19, including its long-term health effects. It’s also made important progress toward the urgent goal of the RECOVER initiative to identify people with or at risk for Long COVID who may be eligible to participate in clinical trials of promising new treatment approaches.
Long COVID remains a puzzling public health challenge. Another recent NIH study published in the journal Annals of Internal Medicine set out to identify people with symptoms of Long COVID, most of whom had recovered from mild-to-moderate COVID-19 . More than half had signs of Long COVID. But, despite extensive testing, the NIH researchers were unable to pinpoint any underlying cause of the Long COVID symptoms in most cases.
So if you’d like to help researchers solve this puzzle, RECOVER is now enrolling adults and kids—including those who have and have not had COVID—at more than 80 study sites around the country.
 Identifying who has long COVID in the USA: a machine learning approach using N3C data. Pfaff ER, Girvin AT, Bennett TD, Bhatia A, Brooks IM, Deer RR, Dekermanjian JP, Jolley SE, Kahn MG, Kostka K, McMurry JA, Moffitt R, Walden A, Chute CG, Haendel MA; N3C Consortium. Lancet Digit Health. 2022 May 16:S2589-7500(22)00048-6.
 A longitudinal study of COVID-19 sequelae and immunity: baseline findings. Sneller MC, Liang CJ, Marques AR, Chung JY, Shanbhag SM, Fontana JR, Raza H, Okeke O, Dewar RL, Higgins BP, Tolstenko K, Kwan RW, Gittens KR, Seamon CA, McCormack G, Shaw JS, Okpali GM, Law M, Trihemasava K, Kennedy BD, Shi V, Justement JS, Buckner CM, Blazkova J, Moir S, Chun TW, Lane HC. Ann Intern Med. 2022 May 24:M21-4905.
COVID-19 Research (NIH)
National COVID Cohort Collaborative (N3C) (National Center for Advancing Translational Sciences/NIH)
Emily Pfaff (University of North Carolina, Chapel Hill)
Melissa Haendel (University of Colorado, Aurora)
NIH Support: National Center for Advancing Translational Sciences; National Institute of General Medical Sciences; National Institute of Allergy and Infectious Diseases