new research findings on covid 19

Long Covid explanation in new study possibly paves way for tests and treatments

Scientists have identified a persistent change in a handful of blood proteins in people with long Covid that indicates that an important part of their immune system remains on high alert for months after an acute infection.

The findings , published Thursday in the journal Science, could help explain what causes the persistent fatigue, brain fog and other debilitating symptoms of long Covid , as well as pave the way for diagnostic tests and potentially, a long-awaited treatment, experts say. 

The study followed 113 Covid patients for up to one year after they were first infected, along with 39 healthy controls. At the six-month mark, 40 patients had developed long Covid symptoms . 

Repeated blood samples turned up important differences in their blood: A group of proteins indicated that a part of the body’s immune system called the complement system remained activated long after it should have returned to normal.

“When you have a viral or bacterial infection , the complement system becomes activated and binds to these viruses and bacteria and then eliminates them,” said Dr. Onur Boyman, a professor of immunology at the University of Zurich in Switzerland and one of the study’s investigators. The system then returns to its resting state, where its regular job is to clear the body of dead cells, he said. 

But if the complement system remains in its microbe-fighting state after the viruses and bacteria are eliminated, “it starts damaging healthy cells,” he said.

“These can be endothelial cells that line the inner layers of blood vessels, the cells of the blood itself, and cells in different organs, like the brain or the lungs,” he continued. The result is tissue damage and microclots in the blood.

Previous studies have documented blood clotting and tissue damage in people with long Covid. “But this research gets at the molecular mechanism of how that might be initiated,” said Akiko Iwasaki, a professor of immunobiology and molecular, cellular and developmental biology at the Yale School of Medicine, who was not involved with the new study.

Tissue damage along with blood clots can lead to the disabling symptoms of long Covid, including an intolerance to exercise.

During exercise, the heart pumps more blood and agitates the endothelial cells inside blood vessels, which are everywhere in the body, Boyman said. 

“In healthy people, normal endothelial cells can take these changes, but the inflamed endothelial cells in long Covid patients cannot,” he said.

Iwasaki noted that microclots can reduce the level of oxygen and nutrients delivered to different organs. 

“If your brain, for example, isn’t getting enough oxygen, obviously there will be a lot of issues with memory, brain fog and fatigue,” she said.

A possible path to tests and treatments 

A little more than 14% of adults in the United States report ever having experienced long Covid, according to the most recent data from the U.S. Census Bureau’s Household Pulse Survey . 

Dr. Monica Verduzco-Gutierrez, chair of rehabilitation medicine at the University of Texas Health Science Center at San Antonio and head of its long Covid clinic, praised the new study.

“Understanding the mechanisms of long Covid is how we’re going to figure out treatments,” she said.

Other studies have also identified potential mechanisms. In  one study , published in the October issue of the journal Cell, researchers suggested that remnants of the virus lingering in the gut of long Covid patients triggered reductions in the neurotransmitter serotonin. Lower serotonin levels, they said, could explain some neurological and cognitive symptoms.  Another study , published in the journal Nature in September by Iwasaki and her colleagues, found that long Covid patients had significantly lower levels of the hormone cortisol than other Covid patients and healthy controls. Cortisol helps people feel alert and awake.

Verduzco-Gutierrez, Iwasaki and Boyman agree that the new research points the way toward developing diagnostic tests and treatment by focusing on the proteins of the complement system.

However, Boyman and his colleagues used cutting-edge, complicated methods for detecting the differences in these proteins that could not be used in a routine diagnostic lab. 

“We need companies already active in diagnostics that have sufficient manpower and financial power” to develop a simplified test, he said. 

Once a test is developed, or with rigorous screening for long Covid patients, pharmaceutical companies could begin clinical trials of potential treatments, Boyman said. Drugs already exist to modulate and inhibit the complement system for very rare immune diseases that affect the kidneys, muscles or nervous system, and they could be tested in long Covid patients, he said.

New drugs could also be developed, Iwasaki said. 

“I think there are a lot of things that we can try in the future,” she said. But first, the results of this study need to be replicated, as with any research, she added.

Verduzco-Gutierrez said she would like to see any future studies follow patients for a longer period of time. “What about people who have had long Covid for three years? We don’t know what their blood looks like,” she said.

Barbara Mantel is an NBC News contributor. She is also the topic leader for freelancing at the Association of Health Care Journalists, writing blog posts, tip sheets and market guides, as well as producing and hosting webinars. Barbara’s work has appeared in CQ Researcher, AARP, Undark, Next Avenue, Medical Economics, Healthline, Today.com, NPR and The New York Times.

Mounting research shows that COVID-19 leaves its mark on the brain, including with significant drops in IQ scores

Chief of Research and Development, VA St. Louis Health Care System. Clinical Epidemiologist, Washington University in St. Louis

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From the very early days of the pandemic, brain fog emerged as a significant health condition that many experience after COVID-19.

Brain fog is a colloquial term that describes a state of mental sluggishness or lack of clarity and haziness that makes it difficult to concentrate, remember things and think clearly.

Fast-forward four years and there is now abundant evidence that being infected with SARS-CoV-2 – the virus that causes COVID-19 – can affect brain health in many ways .

In addition to brain fog, COVID-19 can lead to an array of problems , including headaches, seizure disorders, strokes, sleep problems, and tingling and paralysis of the nerves, as well as several mental health disorders .

A large and growing body of evidence amassed throughout the pandemic details the many ways that COVID-19 leaves an indelible mark on the brain. But the specific pathways by which the virus does so are still being elucidated, and curative treatments are nonexistent.

Now, two new studies published in the New England Journal of Medicine shed further light on the profound toll of COVID-19 on cognitive health .

I am a physician scientist , and I have been devoted to studying long COVID since early patient reports about this condition – even before the term “long COVID” was coined. I have testified before the U.S. Senate as an expert witness on long COVID and have published extensively on this topic.

How COVID-19 leaves its mark on the brain

Here are some of the most important studies to date documenting how COVID-19 affects brain health:

Large epidemiological analyses showed that people who had COVID-19 were at an increased risk of cognitive deficits , such as memory problems.

Imaging studies done in people before and after their COVID-19 infections show shrinkage of brain volume and altered brain structure after infection .

A study of people with mild to moderate COVID-19 showed significant prolonged inflammation of the brain and changes that are commensurate with seven years of brain aging .

Severe COVID-19 that requires hospitalization or intensive care may result in cognitive deficits and other brain damage that are equivalent to 20 years of aging .

Laboratory experiments in human and mouse brain organoids designed to emulate changes in the human brain showed that SARS-CoV-2 infection triggers the fusion of brain cells . This effectively short-circuits brain electrical activity and compromises function.

Autopsy studies of people who had severe COVID-19 but died months later from other causes showed that the virus was still present in brain tissue . This provides evidence that contrary to its name, SARS-CoV-2 is not only a respiratory virus, but it can also enter the brain in some individuals. But whether the persistence of the virus in brain tissue is driving some of the brain problems seen in people who have had COVID-19 is not yet clear.

Studies show that even when the virus is mild and exclusively confined to the lungs, it can still provoke inflammation in the brain and impair brain cells’ ability to regenerate .

COVID-19 can also disrupt the blood brain barrier , the shield that protects the nervous system – which is the control and command center of our bodies – making it “leaky.” Studies using imaging to assess the brains of people hospitalized with COVID-19 showed disrupted or leaky blood brain barriers in those who experienced brain fog.

A large preliminary analysis pooling together data from 11 studies encompassing almost 1 million people with COVID-19 and more than 6 million uninfected individuals showed that COVID-19 increased the risk of development of new-onset dementia in people older than 60 years of age.

Drops in IQ

Most recently, a new study published in the New England Journal of Medicine assessed cognitive abilities such as memory, planning and spatial reasoning in nearly 113,000 people who had previously had COVID-19. The researchers found that those who had been infected had significant deficits in memory and executive task performance.

This decline was evident among those infected in the early phase of the pandemic and those infected when the delta and omicron variants were dominant. These findings show that the risk of cognitive decline did not abate as the pandemic virus evolved from the ancestral strain to omicron.

In the same study, those who had mild and resolved COVID-19 showed cognitive decline equivalent to a three-point loss of IQ. In comparison, those with unresolved persistent symptoms, such as people with persistent shortness of breath or fatigue, had a six-point loss in IQ. Those who had been admitted to the intensive care unit for COVID-19 had a nine-point loss in IQ. Reinfection with the virus contributed an additional two-point loss in IQ, as compared with no reinfection.

Generally the average IQ is about 100. An IQ above 130 indicates a highly gifted individual, while an IQ below 70 generally indicates a level of intellectual disability that may require significant societal support.

To put the finding of the New England Journal of Medicine study into perspective, I estimate that a three-point downward shift in IQ would increase the number of U.S. adults with an IQ less than 70 from 4.7 million to 7.5 million – an increase of 2.8 million adults with a level of cognitive impairment that requires significant societal support.

Another study in the same issue of the New England Journal of Medicine involved more than 100,000 Norwegians between March 2020 and April 2023. It documented worse memory function at several time points up to 36 months following a positive SARS-CoV-2 test.

Parsing the implications

Taken together, these studies show that COVID-19 poses a serious risk to brain health, even in mild cases, and the effects are now being revealed at the population level.

A recent analysis of the U.S. Current Population Survey showed that after the start of the COVID-19 pandemic, an additional 1 million working-age Americans reported having “serious difficulty” remembering, concentrating or making decisions than at any time in the preceding 15 years. Most disconcertingly, this was mostly driven by younger adults between the ages of 18 to 44.

Data from the European Union shows a similar trend – in 2022, 15% of people in the EU reported memory and concentration issues .

Looking ahead, it will be critical to identify who is most at risk. A better understanding is also needed of how these trends might affect the educational attainment of children and young adults and the economic productivity of working-age adults. And the extent to which these shifts will influence the epidemiology of dementia and Alzheimer’s disease is also not clear.

The growing body of research now confirms that COVID-19 should be considered a virus with a significant impact on the brain. The implications are far-reaching, from individuals experiencing cognitive struggles to the potential impact on populations and the economy.

Lifting the fog on the true causes behind these cognitive impairments, including brain fog, will require years if not decades of concerted efforts by researchers across the globe. And unfortunately, nearly everyone is a test case in this unprecedented global undertaking.

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New Long COVID Findings Offer Fuller Picture of Condition

Research published this week suggests that a test for long COVID could be possible.

Study: 1 in 14 Hit With Long COVID

Seth Wenig | AP

A woman walks through a door with a sign asking shoppers to wear masks in New York on Feb. 9, 2022.

COVID-19 isn’t going away – and neither is long COVID. But new data about its prevalence as well as research into biomarkers of long COVID published this week are helping researchers understand what to look for when it comes to the condition.

Data published by the Centers for Disease Control and Prevention’s National Center for Health Statistics on Tuesday was a stark reminder that, while not widespread, some children are affected by long COVID.

Pulling from the 2022 National Health Interview Survey, the data shows that 1.3% of children ever had long COVID as of last year, according to reports from their parents.

The researchers defined long COVID as the “presence of symptoms for at least 3 months after having COVID-19 among those who received either a positive test or a doctor’s diagnosis of COVID-19.”

The rate of long COVID is significantly higher among adults than in children. The survey found that in 2022, about 7% of adults – or about 1 in 14 – reported ever having long COVID. More women reported having had long COVID than men – a trend also observed in children.

Adults ages 35-49 were most likely to have had long COVID, according to the data. Hispanic adults were more likely than Black and white adults to have it.

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The survey also found a higher prevalence of long COVID among Americans living in more rural areas compared with those living in large central metropolitan areas.

There are no approved treatments or tests for the condition. Its cause (or, more likely, causes) remains unknown, though studies have made some progress .

Research published Monday in the journal Nature found that people with long COVID have clear differences in their hormone and immune function when compared to people without the condition. The findings offer hope that a test for the condition is possible.

“These findings are important – they can inform more sensitive testing for long COVID patients and personalized treatments for long COVID that have, until now, not had a proven scientific rationale,” David Putrino, principal investigator of the study, said in a statement . “This is a decisive step forward in the development of valid and reliable blood testing protocols for long COVID.”

The study looked at survey results and blood samples from 270 individuals. It found that the blood of those experiencing long COVID had specific biomarkers, like abnormal T cell activity, reactivation of dormant viruses and low cortisol levels.

“These markers need to be validated in larger studies, but provide a first step in dissecting the disease pathogenesis of long COVID,” Akiko Iwasaki, co-principal investigator of the study, said in a statement.

Coronavirus metrics are increasing in the U.S., underscoring that COVID-19 – as well as long COVID – will be a lasting problem. Health officials have moved away from trying to prevent coronavirus infections, instead shifting their focus to preventing hospitalizations and deaths. Still, many Americans are dealing with repeat infections of COVID-19, which can come with increased risk for a myriad of health problems.

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COVID virus can infect your eyes and damage vision

(Credit: Getty Images )

You are free to share this article under the Attribution 4.0 International license.

The virus that causes COVID-19 can breach the protective blood-retinal barrier, leading to potential long-term consequences in the eye, new research shows.

The blood-retinal barrier is designed to protect our vision from infections by preventing microbial pathogens from reaching the retina where they could trigger an inflammatory response with potential vision loss.

Pawan Kumar Singh, an assistant professor of ophthalmology at the University of Missouri, leads a team researching new ways to prevent and treat ocular infectious diseases.

Using a humanized ACE2 mice model, the team found that SARS-CoV-2, the virus that causes COVID-19, can infect the inside of the eyes even when the virus doesn’t enter the body through the surface of the eyes.

Instead, they found that when viruses enter the body through inhalation, it not only infects organs like lungs, but also reaches highly protected organs like eyes through the blood-retinal barrier by infecting the cells lining this barrier.

“This finding is important as we increase our understanding of the long-term effects of SARS-CoV-2 infection,” says Singh. “Earlier, researchers were primarily focused on the ocular surface exposure of the virus.

“However, our findings reveal that SARS-CoV-2 not only reaches the eye during systemic infection but induces a hyperinflammatory response in the retina and causes cell death in the blood-retinal barrier. The longer viral remnants remain in the eye, the risk of damage to the retina and visual function increases.”

Singh also discovered that extended presence of SARS-CoV-2 spike antigen can cause retinal microaneurysm, retinal artery and vein occlusion , and vascular leakage.

“For those who have been diagnosed with COVID-19, we recommend you ask your ophthalmologist to check for signs of pathological changes to the retina,” Singh says. “Even those who were asymptomatic could suffer from damage in the eyes over time because of COVID-19 associated complications.”

While viruses and bacteria have been found to breach the blood-retinal-barrier in immunocompromised people, this research is the first to suggest that the virus that causes COVID-19 could breach the barrier even in otherwise healthy individuals, leading to an infection that manifests inside the eye itself.

Immunocompromised patients or those with hypertension or diabetes may experience worse outcomes if they remain undiagnosed for COVID-19 associated ocular symptoms.

“Now that we know the risk of COVID-19 to the retina, our goal is to better understand the cellular and molecular mechanisms of how this virus breaches the blood-retinal barrier and associated pathological consequences in hopes of informing development of therapies to prevent and treat COVID-19 induced eye complications before a patient’s vision is compromised,” Singh says.

The study appears in the journal PLOS Pathogens .

The National Institutes of Health/National Eye Institute and the University of Missouri funded the work.

Source: University of Missouri

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NIH to open long COVID clinical trials to study sleep disturbances, exercise intolerance, and post exertional malaise

Part of the NIH RECOVER Initiative, trials will test four treatments.

The National Institutes of Health (NIH) will launch clinical trials to investigate potential treatments for long-term symptoms after COVID-19 infection, including sleep disturbances, exercise intolerance and the worsening of symptoms following physical or mental exertion known as post-exertional malaise (PEM). The mid-stage trials, part of NIH’s Researching COVID to Enhance Recovery (RECOVER) Initiative, will join six other RECOVER studies currently enrolling participants across the United States testing treatments to address viral persistence, neurological symptoms, including cognitive dysfunction (like brain fog) and autonomic nervous system dysfunction. The new trials will enroll approximately 1,660 people across 50 study sites to investigate potential treatments for some of the most frequent and burdensome symptoms reported by people suffering from long COVID.

“The group of symptoms these trials will try to alleviate are truly disruptive and devastating for so many people struggling with long COVID,” said Walter J. Koroshetz, M.D., director of NIH’s National Institute of Neurological Disorders and Stroke, and co-lead of the RECOVER Initiative. “When people can’t get reliable sleep, can’t exert themselves and feel sick following tasks that used to be simple, the physical and mental anguish can lead to feelings of utter helplessness. We urgently need to come up with answers to help those struggling with long COVID feel whole again.”

RECOVER-SLEEP clinical trials will soon begin enrolling participants and include:

• A trial to test two drugs (modafinil and solriamfetol) approved by the Food and Drug Administration to treat people who have problems staying awake during the day, known as hypersomnia. These medications are well-known but have not been studied widely in people with long COVID. Participants will be randomly assigned to receive either the active study drug or a placebo control for eight to 10 weeks, depending on the assigned study drug.
• A trial to test potential treatments for complex sleep disturbances due to long COVID, including melatonin, an over-the-counter supplement commonly used to treat people with sleep disorders and general insomnia; and light therapy, which is used to help people reset their sleep cycles. Participants will be randomly assigned to receive either melatonin or a placebo control, and either high-intensity (active) light therapy or low-intensity (placebo) light therapy for eight weeks. 

RECOVER-ENERGIZE clinical trials will soon begin enrolling participants and include:

• A trial to test a program that combines exercise training, strength and flexibility training,  education, and social support, collectively known as personalized cardiopulmonary rehabilitation. The program is designed to help people who experience exercise intolerance with symptoms such as shortness of breath and fatigue during exercise after having COVID-19.  All participants in RECOVER-ENERGIZE trials will be screened for PEM. Participants who are identified as having PEM, via a validated PEM questionnaire, will not be included in this trial. Participants will be randomly assigned to receive either personalized cardiopulmonary rehabilitation or basic exercise education for three months.
• A trial to test a program known as structured pacing, which is designed to help participants with PEM identify, control, and minimize symptoms that developed after having COVID-19 by regulating or pacing their daily activities. Currently, structured pacing is the only intervention used to treat PEM. The trial will not include any exercise training or physical movement to protect participants from developing worsened symptoms of PEM. Participants will be randomly assigned to receive either structured pacing with a trained coach or basic PEM education for three months.

All four trials were developed using comprehensive feedback from the community and in close partnership with patient representatives, whose insights were especially important for the PEM trial. The PEM trial was developed to address concerns expressed by patient advocacy groups about patient safety, and to better understand how this study program may help improve PEM symptoms.

“Structured pacing is currently the only intervention used to prevent post-exertional malaise, so we hope to test its effectiveness and determine how to best guide patients regarding activity management,” said Lucinda Bateman, M.D., an expert in PEM and founder of the Bateman Horne Center, Salt Lake City, a facility specializing in treating people with ME/CFS, long COVID and fibromyalgia.

Diversity among trial participants is a high priority for the RECOVER Initiative. To support diverse and inclusive representation, study sites are chosen based on geographic location, their connection to communities, and track record for enrolling diverse research participants. Teams at the selected study sites will recruit participants from their health systems and surrounding communities.

Sites currently activated for each trial can be found on ClinicalTrials.gov (RECOVER-SLEEP  NCT06404086 ,  NCT06404099 ,  NCT06404112 and RECOVER-ENERGIZE NCT06404047 ,  NCT06404060 ,  NCT06404073 ). New sites will be added to clinicaltrials.gov as they begin enrolling participants.

With the launch of these four studies, RECOVER is currently testing 13 treatments across eight clinical trials and continues to enroll participants. Those interested in learning more about RECOVER clinical trials should visit trials.recovercovid.org .

About RECOVER : The National Institutes of Health Researching COVID to Enhance Recovery (NIH RECOVER) Initiative brings together clinicians, scientists, caregivers, patients, and community members to understand, diagnose, and treat long COVID. RECOVER has created one of the largest and most diverse groups of long COVID study participants in the world. In addition, RECOVER clinical trials are testing potential interventions across five symptom focus areas. For more information, please visit recovercovid.org . 

HHS Long COVID Coordination: This work is a part of the National Research Action Plan , a broader government-wide effort in response to the Presidential Memorandum directing the Secretary for the Department of Health and Human Services to mount a full and effective response to long COVID. Led by Assistant Secretary for Health Admiral Rachel Levine, the Plan and its companion Services and Supports for Longer-term Impacts of COVID-19 report lay the groundwork to advance progress in the prevention, diagnosis, treatment, and provision of services for individuals experiencing long COVID.

About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov .

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U.S. Tightens Rules on Risky Virus Research

A long-awaited new policy broadens the type of regulated viruses, bacteria, fungi and toxins, including those that could threaten crops and livestock.

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By Carl Zimmer and Benjamin Mueller

The White House has unveiled tighter rules for research on potentially dangerous microbes and toxins, in an effort to stave off laboratory accidents that could unleash a pandemic.

The new policy, published Monday evening, arrives after years of deliberations by an expert panel and a charged public debate over whether Covid arose from an animal market or a laboratory in China.

A number of researchers worried that the government had been too lax about lab safety in the past, with some even calling for the creation of an independent agency to make decisions about risky experiments that could allow viruses, bacteria or fungi to spread quickly between people or become more deadly. But others warned against creating restrictive rules that would stifle valuable research without making people safer.

The debate grew sharper during the pandemic, as politicians raised questions about the origin of Covid. Those who suggested it came from a lab raised concerns about studies that tweaked pathogens to make them more dangerous — sometimes known as “gain of function” research.

The new policy, which applies to research funded by the federal government, strengthens the government’s oversight by replacing a short list of dangerous pathogens with broad categories into which more pathogens might fall. The policy pays attention not only to human pathogens, but also those that could threaten crops and livestock. And it provides more details about the kinds of experiments that would draw the attention of government regulators.

The rules will take effect in a year, giving government agencies and departments time to update their guidance to meet the new requirements.

“It’s a big and important step forward,” said Dr. Tom Inglesby, the director of the Johns Hopkins Center for Health Security and a longtime proponent of stricter safety regulations. “I think this policy is what any reasonable member of the public would expect is in place in terms of oversight of the world’s most transmissible and lethal organisms.”

Still, the policy does not embrace the most aggressive proposals made by lab safety proponents, such as creating an independent regulatory agency. It also makes exemptions for certain types of research, including disease surveillance and vaccine development. And some parts of the policy are recommendations rather than government-enforced requirements.

“It’s a moderate shift in policy, with a number of more significant signals about how the White House expects the issue to be treated moving forward,” said Nicholas Evans, an ethicist at University of Massachusetts Lowell.

Experts have been waiting for the policy for more than a year. Still, some said they were surprised that it came out at such a politically fraught moment . “I wasn’t expecting anything, especially in an election year,” Dr. Evans said. “I’m pleasantly surprised.”

Under the new policy, scientists who want to carry out experiments will need to run their proposals past their universities or research institutions, which will to determine if the work poses a risk. Potentially dangerous proposals will then be reviewed by government agencies. The most scrutiny will go to experiments that could result in the most dangerous outcomes, such as those tweaking pathogens that could start a pandemic.

In a guidance document , the White House provided examples of research that would be expected to come under such scrutiny. In one case, they envisioned scientists trying to understand the evolutionary steps a pathogen needed to transmit more easily between humans. The researchers might try to produce a transmissible strain to study, for example, by repeatedly infecting human cells in petri dishes, allowing the pathogens to evolve more efficient ways to enter the cells.

Scientists who do not follow the new policy could become ineligible for federal funding for their work. Their entire institution may have its support for life science research cut off as well.

One of the weaknesses of existing policies is that they only apply to funding given out by the federal government. But for years , the National Institutes of Health and other government agencies have struggled with stagnant funding, leading some researchers to turn instead to private sources. In recent years, for example, crypto titans have poured money into pandemic prevention research.

The new policy does not give the government direct regulation of privately funded research. But it does say that research institutions that receive any federal money for life-science research should apply a similar oversight to scientists doing research with support from outside the government.

“This effectively limits them, as the N.I.H. does a lot of work everywhere in the world,” Dr. Evans said.

The new policy takes into account the advances in biotechnology that could lead to new risks. When pathogens become extinct, for example, they can be resurrected by recreating their genomes. Research on extinct pathogens will draw the highest levels of scrutiny.

Dr. Evans also noted that the new rules emphasize the risk that lab research can have on plants and animals. In the 20th century, the United States and Russia both carried out extensive research on crop-destroying pathogens such as wheat-killing fungi as part of their biological weapons programs. “It’s significant as a signal the White House is sending,” Dr. Evans said.

Marc Lipsitch, an epidemiologist at Harvard and a longtime critic of the government’s policy, gave the new one a grade of A minus. “I think it’s a lot clearer and more specific in many ways than the old guidance,” he said. But he was disappointed that the government will not provide detailed information to the public about the risky research it evaluates. “The transparency is far from transparent,” he said.

Scientists who have warned of the dangers of impeding useful virus research were also largely optimistic about the new rules.

Gigi Gronvall, a biosafety specialist at the Johns Hopkins Bloomberg School of Public Health, said the policy’s success would depend on how federal health officials interpreted it, but applauded the way it recognized the value of research needed during a crisis, such as the current bird flu outbreak .

“I was cautiously optimistic in reading through it,” she said of the policy. “It seems like the orientation is for it to be thoughtfully implemented so it doesn’t have a chilling effect on needed research.”

Anice Lowen, an influenza virologist at Emory University, said the expanded scope of the new policy was “reasonable.” She said, for instance, that the decision not to create an entirely new review body helped to alleviate concerns about how unwieldy the process might become.

Still, she said, ambiguities in the instructions for assessing risks in certain experiments made it difficult to know how different university and health officials would police them.

“I think there will be more reviews carried out, and more research will be slowed down because of it,” she said.

Carl Zimmer covers news about science for The Times and writes the Origins column . More about Carl Zimmer

Benjamin Mueller reports on health and medicine. He was previously a U.K. correspondent in London and a police reporter in New York. More about Benjamin Mueller

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• Published: 06 May 2024

Vaccine effectiveness against emerging COVID-19 variants using digital health data

• Tanner J. Varrelman   ORCID: orcid.org/0000-0002-8766-0129 1 ,
• Benjamin Rader 1 , 2 ,
• Christopher Remmel 1 ,
• Gaurav Tuli 1 ,
• Aimee R. Han   ORCID: orcid.org/0000-0001-8927-3432 1 ,
• Christina M. Astley   ORCID: orcid.org/0000-0002-5063-8470 1 , 3 , 4 , 5 &
• John S. Brownstein   ORCID: orcid.org/0000-0001-8568-5317 1 , 4  

Communications Medicine volume  4 , Article number:  81 ( 2024 ) Cite this article

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• Computational biology and bioinformatics

Participatory surveillance of self-reported symptoms and vaccination status can be used to supplement traditional public health surveillance and provide insights into vaccine effectiveness and changes in the symptoms produced by an infectious disease. The University of Maryland COVID Trends and Impact Survey provides an example of participatory surveillance that leveraged Facebook’s active user base to provide self-reported symptom and vaccination data in near real-time.

Here, we develop a methodology for identifying changes in vaccine effectiveness and COVID-19 symptomatology using the University of Maryland COVID Trends and Impact Survey data from three middle-income countries (Guatemala, Mexico, and South Africa). We implement conditional logistic regression to develop estimates of vaccine effectiveness conditioned on the prevalence of various definitions of self-reported COVID-like illness in lieu of confirmed diagnostic test results.

We highlight a reduction in vaccine effectiveness during Omicron-dominated waves of infections when compared to periods dominated by the Delta variant (median change across COVID-like illness definitions: −0.40, IQR[−0.45, −0.35]. Further, we identify a shift in COVID-19 symptomatology towards upper respiratory type symptoms (i.e., cough and sore throat) during Omicron periods of infections. Stratifying COVID-like illness by the National Institutes of Health’s (NIH) description of mild and severe COVID-19 symptoms reveals a similar level of vaccine protection across different levels of COVID-19 severity during the Omicron period.

Conclusions

Participatory surveillance data alongside methodologies described in this study are particularly useful for resource-constrained settings where diagnostic testing results may be delayed or limited.

Plain language summary

Surveys that are sent out to users of social media can be used to supplement traditional methods to monitor the spread of infectious diseases. This has the potential to be particularly useful in areas where other data is unavailable, such as areas with less surveillance of infectious disease prevalence and access to infectious disease diagnostics. We used data from a survey available to users of the social media platform Facebook to collect information about any potential symptoms of COVID-19 infection and vaccines received during the COVID-19 pandemic. We found a potential reduction in vaccine effectiveness and change in symptoms when the Omicron variant was known to be circulating compared to the earlier Delta variant. This method could be adapted to monitor the spread of COVID-19 and other infectious diseases in the future, which might enable the impact of infectious diseases to be recognized more quickly.

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Introduction.

Timely identification of alterations in vaccine effectiveness (VE) with the emergence of novel COVID-19 variants, such as Omicron, is important for informing the global public health response. The attributable risk proportion of vaccine-preventable diseases is often estimated using relative risk measures obtained from cohort studies or odds ratios determined through case-control designs, which typically rely on gold-standard diagnostic testing 1 , 2 . These studies are conducted retrospectively, leading to a lag between variant emergence and VE estimates. In an effort to provide timely VE insights, monitoring systems have been developed that leverage digital health data 3 , 4 . However, even these real-time methodologies are bounded by some form of diagnostic testing data, whether it be self-reported or through other means of collection. While resource-rich locales across the world have managed to scale up diagnostic testing to inform pandemic response efforts, many low-and middle-income countries (LMICs) have struggled to establish widespread testing 5 , 6 , therefore limiting the applicability of current VE monitoring systems. Alternatively, digital health surveys of self-reported symptoms and vaccination status provide a data source that may be used in place of limited/delayed testing data 7 , 8 , 9 .

In this study, we use data from the University of Maryland Global COVID Trends and Impact Survey (UMD-CTIS) to develop a methodology to simultaneously characterize potential changes in VE and COVID-19 symptomatology for Delta and Omicron-dominated periods of infections. UMD-CTIS is a digital health survey that leveraged Facebook’s active user base, providing cross-sectional survey data in near real-time from 114 countries, starting in 2020 and ending in 2022. Our analyses utilize aggregate data from three MICs that were selected based on the quality of UMD-CTIS data and the presence of distinct Delta and Omicron periods of infections. The selected countries include Guatemala, Mexico, and South Africa. Our analyses of this data reveal reduced vaccine effectiveness against suspected COVID-19 infection during the Omicron period compared to Delta, as well as a shift towards more upper respiratory-type symptoms like cough and sore throat.

Syndromic surveillance data

The University of Maryland Global COVID Trends and Impact Survey (UMD-CTIS), in partnership with Facebook, is a cross-sectional survey that sampled Facebook’s active user base on a daily basis. Facebook users were presented an invitation at the top of their news feed, inviting them to participate in the survey. It is important to note that survey invitations did not include any type of incentive, and participation was driven purely by individuals’ willingness to contribute to digital health. If an individual decided to accept the invitation, they were navigated off of the Facebook platform to the digital health survey hosted by Qualtrics, with data collection being performed by the Joint Program in Survey Methodology at the University of Maryland. On the Qualtrics survey itself, respondents were shown the consent page explaining the purpose of the research to gain a better public understanding of where and how the coronavirus pandemic is spreading, that the survey would take 3–5 min, and that their responses would remain confidential and anonymous. After providing informed consent and confirmation of being at least 18 years of age, respondents could proceed with the survey. Survey respondents and non-respondents were entered back into the sampling pool after a duration of a few weeks or months, depending on the sample size for a given area. Survey data included self-reported information such as demographics, recent symptoms, and COVID-19 vaccination status. While Facebook acts as the survey sampling frame, the company cannot access individually identified respondent answers. Further, to work with these data, institutions must have a signed Data Use Agreement (data access and survey questions available https://covidmap.umd.edu ) 7 , 10 , which our institution signed in order to access and analyze the UMD-CTIS data. Boston Children’s Hospital Institutional Review Board (P00023700) approved this study using UMD-CTIS data. Additional details on the survey design, methodology, and validation can be found in Astley et al. (2021) 7 .

To select the study locations, we began by focusing on countries that met three criteria: they are included in the UMD-CTIS sample, have encountered distinct waves of COVID-19 infections primarily driven by the Delta and Omicron variants, and are considered a low or middle-income country as described by the Organization for Economic Co-operation and Development (OECD). Next, we visualized the time-series symptom data and ruled out countries where the UMD-CTIS data was noticeably erratic.

Using peak detection (Python (3.8.2), scipy.signal.argrelextrema (1.7.1), order parameter = 70) for all CLI time series (April 2021–February 2022), we infer 2-week consensus variant periods prior to each peak, for Delta and Omicron, respectively, for Guatemala (peak date September 13, 2021 [survey No. 4137] and peak date February 2, 2022 [survey No. 2387]), South Africa (July 22, 2021 [survey No. 7371] and December 19, 2021 [survey No. 5320]), and Mexico (August 22, 2021 [survey No. 52775] and January 26, 2022 [survey No. 71990]), that coincided with >80% variant share per public reports 11 .

Statistics and reproducibility

We utilize conditional logistic regression to estimate the attributable risk proportion (ARP) for illness in 2-dose vaccinated individuals (clogit function with method=’approximate’, R (4.1.1), survival library (3.2-13)). VE is given by VE = ARP ≈ 1−OR. We consider exposure as the vaccination status of a respondent (unvaccinated vs. 2-dose vaccinated), and the outcome as to whether a respondent reported CLI in past 14 days, with missing symptoms assumed absent. We also include strata for dichotomized age (>44 years), gender (male/female), and country of the survey respondent to limit potential confounding and differences in country-level sampling. Importantly, UMD-CTIS does not collect data on vaccine formulation. Consequently, we cannot definitively determine whether a single dose of any specific vaccine within our dataset consistently provides full protection, as seen with the Janssen COVID-19 vaccine formulation. Therefore, we have chosen not to include individuals who have received only one dose in this study. Age and gender were dichotomized in order to maintain sufficient sample sizes per stratum. We do not filter the individual vaccine effectiveness estimates by p -value, as we are interested in the group behavior of the CLI definitions and not the hypothesis of whether a single definition of CLI produces a statistically significant vaccine effectiveness estimate. Moreover, to maintain the same number of data points for each of our comparisons, we do not remove outlier data from the analyses in this study.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

To estimate VE, we adapted case-control methods 1 for prevalent COVID-like illness (CLI) as a proxy for confirmed COVID-19 cases. Therefore, our estimates of VE measure a vaccine’s ability to prevent suspected symptomatic infections defined by CLI. To allow for changes in variant-specific symptomatology, we iterate across all possible CLI defined by 66 pair-wise combinations of 12 self-reported symptoms (fever, cough, difficulty breathing, fatigue, stuffy or runny nose, aches or muscle pain, sore throat, chest pain, nausea, loss of smell or taste, headache, chills). We then cluster the vaccine effectiveness estimates according to a single symptom of interest and evaluate the median vaccine effectiveness across all CLI definitions in the cluster. As an example, using a COVID-19-specific symptom (loss of smell or taste) as an anchor symptom, we evaluate VE estimates for all CLI definitions inclusive of this symptom during Delta and Omicron waves of infections, resulting in VE estimates for 11 pairwise combinations of symptoms. Consistent with previous estimates of VE that used PCR test data as the outcome 2 , our analyses reveal a median VE Delta of 0.77, IQR[0.76, 0.80] (Fig.  1 a, triangle). In comparison, analyzing the data from the Omicron period reveals a median VE Omicron of 0.47, IQR[0.41, 0.53] (Fig.  1 a, circle). Further expanding the approach to all CLI definitions reveals a median VE Delta of 0.71, IQR[0.65, 0.75] (Fig.  1 b). In contrast, the VE Omicron estimate is even lower (median 0.29, IQR[0.20, 0.38]). Notably, our findings align with those from a recent meta-analysis study focused on real-world vaccine effectiveness for fully vaccinated individuals. This study reported a VE of 70.9% (95% CI, 68.9–72.7) against Delta infections and a VE of 23.5% (95% CI, 17.0–29.5) against Omicron variant infections 12 . To understand how VE estimates for each CLI definition vary by wave, we take the difference between the two VE period estimates (VE Omicron −VE Delta ) for each CLI definition. Doing so reveals a median within-CLI definition change of −0.40, IQR[−0.45, −0.35] (Fig.  2 a), suggesting lower VE Omicron regardless of the CLI definition that is used. Additionally, we find that the pattern of change in VE across CLI definitions is similar when evaluating individual country estimates (see Supplementary Fig.  1 ).

a VE estimates for symptoms paired with the loss of smell or taste for the Delta (triangle) and Omicron (circle) periods. 95% confidence intervals are calculated for each VE estimate, with Delta and Omicron period estimates derived from 64,283 and 79,697 survey responses, respectively. b Box and whisker plot of VE estimates across all 66 possible CLI defined by pairwise combinations of symptoms for Delta and Omicron periods. The box represents the interquartile range (IQR) of estimates, with the horizontal line inside the box indicating the median. The whiskers extend to the largest/smallest values up to 1.5 times the IQR. Outlier values are represented as points. The sample size for each VE estimate is consistent with the sample sizes described in panel ( a ).

a Distribution of within-CLI change (VE Omicron −VE Delta ) across all CLI definitions. b Distributions of VE Omicron −VE Delta among CLI definitions within each anchor symptom. Each box-plot contains estimates for an anchor symptom paired with the 11 other symptoms. Box-plots are ordered according to the magnitude of the median change, with the median across all VE indicated by the gray dashed line. Each box represents the interquartile range (IQR) of estimates, with the horizontal line inside the box indicating the median. The whiskers extend to the largest/smallest values up to 1.5 times the IQR. Outlier values are represented as points. Each VE estimate from the Delta and Omicron periods is derived from 64,283 and 79,697 survey responses, respectively.

To identify potential alterations in COVID-19 symptomatology, we evaluate the change in VE estimates for CLI definitions with a single anchor symptom, like loss of smell and taste. We reason that if symptoms are similar across variants, the within-anchor median change in VE will be similar across anchor symptoms. Our analyses provide evidence for a potential change in COVID-19 symptomatology from the Delta period to the Omicron period, as we note that some symptoms have more or less decline in VE (Fig.  2 b). Specifically, we find that CLI definitions that include loss of smell or taste have the smallest median change in VE (median: −0.31, IQR[−0.34, −0.28]), while definitions with the largest median change include a cough, or sore throat (cough median: −0.49, IQR[−0.52, −0.45]; sore throat median: −0.47, IQR[−0.49, −0.45]). The observed pattern of change in VE across anchor symptoms is similar when evaluating VE estimates from individual countries (see Supplementary Fig.  2) , however, with increased uncertainty in estimates as measured by the span of anchor symptom distributions (see  Supplementary Results ). Similarly, a survey-based study that used PCR testing data as the outcome demonstrated a shift away from symptomatology that includes loss of smell or taste and towards upper-respiratory type symptoms (i.e., sore throat) during the Omicron period 13 . Furthermore, a study conducted in Jalisco, Mexico, analyzed reported symptoms for confirmed infections with wild-type SARS-CoV-2, Delta, and Omicron variants, revealing that Omicron infections were linked to a higher incidence of runny nose and sore throat, aligning with the findings of our country-level analysis for Mexico (see Supplementary Fig.  3) 14 . These results corroborate our overall findings, which also identified increased reporting of sore throat during a wave of COVID-19 infections dominated by the Omicron variant. Collectively, these findings suggest a shift in symptomatology associated with the Omicron variant towards more upper respiratory-type symptoms.

In addition to providing insights into changes in COVID-19 symptomatology, the VE estimates also include information about a vaccine’s ability to protect against COVID-19 illness presenting at different levels of severity as defined by pairwise combinations of symptoms. Importantly, we do not have information about the true severity of each respondent’s reported illness, and we instead infer severity based on the presence and absence of key symptoms. For instance, all CLI definitions that include at least a fever, cough, aches or muscle pain, sore throat, nausea, loss of smell or taste, or a headache in the absence of difficulty breathing or chest pain are considered mild syndromes. However, according to the NIH, CLI definitions that include difficulty breathing or chest pain are considered more severe forms of illness 15 . To understand potential changes in VE against mild and severe COVID-19 syndromes, we partition our CLI-informed VE estimates according to the above classifications. As a result, we end up with 42 mild and 21 severe definitions of CLI. We find that severe definitions of illness were more protected than mild definitions during the Delta period (median severe VE: 0.74, IQR[0.70, 0.79], median mild VE: 0.54, IQR[0.45, 0.64]) (Fig.  3 ). However, protection against mild and severe illness was similar during Omicron (median severe VE: 0.30, IQR[0.25, 0.38], median mild VE: 0.22, IQR[0.16, 0.33]). Importantly, VE against severe illness may appear higher, as vaccines are producing milder illness when an individual is infected with COVID-19 16 , making it seem as if VE against mild illness is less effective. During the Delta wave of infections, we observed a total of 13,220 reports of mild illness and 5316 reports of severe illness. In contrast, during the Omicron wave of infections, there were 24,408 reports of mild illness and 10,234 reports of severe illness.

VE estimates for pairwise combinations of symptoms that include a fever, cough, aches or muscle pain, sore throat, nausea, loss of smell or taste, or a headache in the absence of difficulty breathing or chest pain (mild illness), and pairwise combinations of symptoms that include difficulty breathing or chest pain (severe illness). Each box represents the interquartile range (IQR) of estimates, with the horizontal line inside the box indicating the median. The whiskers extend to the largest/smallest values up to 1.5 times the IQR. Outlier values are represented as points. Each VE estimate from the Delta and Omicron periods is derived from 64,283 and 79,697 survey responses, respectively.

It is critical to note that our estimates of VE measure the preventable syndrome attributed to receiving 2-doses of vaccine and represent only one of many components that contribute to true vaccine effectiveness. For instance, we are unable to account for asymptomatic breakthrough infections, and we do not have information on natural immunity among the unvaccinated nor on vaccine formulation or timing for the vaccinated. Therefore, we do not have enough information to distill whether changes in VE are caused by waning vaccine immunity, or increased penetration of an emerging variant. To this end, we would suggest that future digital health surveys include information on vaccine formulation, the general timing of vaccination, as well as information on booster doses that have been administered. While quickly adapting a digital health survey is a monumental task, it would enhance the capabilities of methods such as those described in this study. Furthermore, our VE estimates are solely derived from self-reported survey data and are thus vulnerable to a range of biases 17 . For instance, self-report bias is likely influenced by the perception around COVID-19 vaccination at a given time for a given locale. Even so, a U.S.-based survey that incorporated viral testing demonstrated that self-reported vaccination is a strong predictor for true vaccination status 18 , thus providing support for self-reported measures. Further, our estimates rely on the assumption that the range of self-reported CLI definitions defined in this study is a valid proxy for incident COVID-19 infection. Consequently, our VE estimates may be an underestimation if CLI is capturing non-COVID illness. We limit this assumption by selecting time periods reflective of when COVID-19 is circulating within the unvaccinated population of survey respondents for each country.

Although the assumptions mentioned above limit the interpretation of our VE estimates, the methodology still demonstrates notable strengths that should not be discounted. For example, simple surveys that collect self-reported symptoms and vaccination status can be collected rapidly and at a fraction of the cost of traditional surveillance measures 19 . Moreover, while we performed the retrospective analysis with knowledge of specific COVID-19 variants, CLI-informed VE estimates can be derived during suspected variant spread, with careful contextualization of a country’s epidemiological situation (i.e., absence of co-circulating pathogens and sufficient geographic coverage of surveys). In the case of UMD-CTIS, there was a two-week delay between survey completion and its availability for our modeling, allowing us to use it as a valuable near-real-time dataset for VE analyses. It is critical to note that UMD-CTIS collected a substantial number of survey samples from numerous countries, enabling meaningful insights into COVID-19. However, some countries within the UMD-CTIS sample exhibited noisy data, characterized by high variability in the number of reported CLI instances between time steps, which limited the utility of these specific datasets. While UMD-CTIS has yielded valuable data from a wide range of countries, it’s important to acknowledge that the determination of survey sampling intensity, size, and other attributes of sampling can impact the reliability and applicability of findings. To truly understand the minimum number of samples required for robust statistical analyses, further research, and investigation into these sampling parameters are essential. Such efforts will not only enhance the effectiveness of syndromic surveillance but also contribute to more accurate and comprehensive insights into COVID-19 dynamics.

Historically, understanding the impact of infectious diseases, including the effectiveness of vaccination, has relied on detailed clinical data, often gathered through sentinel surveillance networks 20 . For example, the CDC’s U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet) provides information about symptom prevalence for suspected flu cases across the United States over time. While an invaluable resource, ILINet is limited to individuals seeking medical care due to its reliance on sentinel providers for data collection. Therefore, individuals who lack access to such sentinel providers or those who do not seek care will not be represented in these data. Consequently, epidemiological parameters derived from these data may not be entirely representative of the population of interest. Participatory digital surveillance systems like Flu Near You, the ZOE App, and UMD-CTIS enable broader symptom tracking by collecting data directly from the public 3 , 21 . These community-based data sources can provide complementary signals to those derived through clinical data-dependent systems like ILINet 22 . Our analysis of self-reported symptoms from UMD-CTIS demonstrates how digital health data can also be rapidly utilized to infer symptomatic shifts across populations, with the advantage of timeliness and scope beyond only those seeking care. While this application does not provide the same level of clinical confirmation as traditional studies, combining evidence from both clinical and digital participatory data sources allows for earlier response guidance while gold-standard data are collected. For instance, applying our methodology of detecting potential changes in symptomatology could help direct early public health mitigation strategies.

The COVID-19 pandemic exposed vulnerabilities in health infrastructure, particularly for LMICs that struggled to establish testing facilities 8 , needed to support real-time epidemiological parameter estimation that depends on diagnostic testing results. Leveraging the power of global participatory epidemiology in the form of digital health surveys 23 has the potential to supplement these critical testing gaps. Thus, our methods of using self-reported symptom data to understand VE and changes in symptomatology is a powerful rapid response tool, that can provide the medical community with timely insights into emerging variants. Due to our agnostic approach in defining a syndrome (i.e., all pairwise symptoms), the utility of our methods goes beyond COVID-19 and can be applied to other upper-respiratory illnesses and/or locations to support response to emerging threats.

Data availability

To access the raw data used in this manuscript, a request must be submitted to the Facebook Data for Good website: https://dataforgood.facebook.com/dfg/docs/covid-19-trends-and-impact-survey-request-for-data-access . The Global UMD-CTIS Open Data API, Microdata Repository, and contingency tables are available from The University of Maryland Social Data Science Center Global COVID-19 Trends and Impact Survey website ( https://covidmap.umd.edu ). The results of the conditional logistic regression can be found in Supplemental Data  1 and Supplemental Data  2 .

Code availability

The R and Python code used to perform the analyses in this study is available at https://doi.org/10.5281/zenodo.10775701 24 .

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Acknowledgements

This work was supported by a Facebook Sponsored Research Agreement (T.J.V., B.R., C.R., G.T., A.H., C.M.A., J.S.B., INB1116217). Authors report research grant funding from the Massachusetts Consortium on Pathogen Readiness (J.S.B.), the Rockefeller Foundation (J.S.B.), and the National Institutes of Health (CMA, K23 DK120899) during the conduct of the study.

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Tanner J. Varrelman, Benjamin Rader, Christopher Remmel, Gaurav Tuli, Aimee R. Han, Christina M. Astley & John S. Brownstein

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Christina M. Astley

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T.J.V., B.R., C.M.A., and J.B. conceived the study. T.J.V. and G.T. analyzed the data. T.J.V, B.R., C.M.A., and J.B. drafted the manuscript. T.J.V., B.R., G.T., C.R., A.H., C.M.A., and J.B. reviewed and edited the manuscript. All authors approved of the final manuscript.

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Varrelman, T.J., Rader, B., Remmel, C. et al. Vaccine effectiveness against emerging COVID-19 variants using digital health data. Commun Med 4 , 81 (2024). https://doi.org/10.1038/s43856-024-00508-9

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Scripps Research Institute researchers investigated SARS-CoV-2 genomics and molecular epidemiology in Southern California, collaborating with the CDC SPHERES program, California COVIDNet, and county and local public health laboratories. Awarded in 2020, this project expanded collaboration with California laboratories to improve laboratory and bioinformatic methods for cost-effective, high-throughput sequencing.

Findings on SARS-CoV-2 surveillance and investigations

This project:

• Determined there were several independent introductions of the highly transmissible B.1.1.7 variant in the United States which spread to most states within months. 1
• Described the emergence of SARS-CoV-2 and the role of superspreading during large-scale events during the early outbreak in the United States by using mobility and genomic data. 2
• Developed ViReflow, a user-friendly pipeline enabling rapid analysis of viral sequence dataset. Developed specifically in response to the COVID-19 pandemic, ViReflow is general to any viral pathogen. 3
• Evaluated the amount of SARS-CoV-2 that could be detected from touched versus non-touched indoor surfaces. 4
• Developed improved virus concentration protocols, as well as analysis software for wastewater surveillance. As a result, it was possible to detect emerging variants of concern up to 14 days earlier than through clinical testing. 5
• Developed a rapid and inexpensive pipeline using a molecular test to detect and quantify RNA for SARS-CoV-2. The processing capacity was 6,000 samples per day with next-day result turnaround times. 6
• Developed Outbreak.info , an open-source database that tracks more than 40 million combinations of lineages and individual mutations, such as those on the surface of SARS-CoV-2 that helps the virus enter human cells. Then the data are used to provide insights for researchers, public health officials, and the general public. 7
• Developed Outbreak.info Research Library , a searchable interface of COVID-19 and SARS-CoV-2 resources including publications, clinical trials, datasets, protocols, and other resources. 8

New SARS-CoV-2 dashboards and websites

• In partnership with SEARCH alliance, conducted SARS-CoV-2 wastewater monitoring for the San Diego region and provided weekly reporting publicly.
• Hosted a web portal, Outbreak.info , that analyzes and visualizes SARS-CoV-2 genomic data, and Outbreak.info Research Library, and a searchable interface of COVID-19 and SARS-CoV-2 resources including publications, clinical trials, datasets.

New and improved sequencing software tools

• Developed ViReflow, a user-friendly viral consensus sequence reconstruction pipeline enabling rapid analysis of viral sequence data set. 9
• Developed Outbreak.info —a web portal that analyzes and visualizes SARS-CoV-2 genomic data—and Outbreak.info Research Library —a searchable interface of COVID-19 and SARS-CoV-2 resources including publications, clinical trials, datasets. 7 8
• Developed Freyja , an analysis framework for SARS-CoV-2 wastewater sequence data.
• Continues to develop and maintain open-source software for data streaming and analysis, including iVar and INSPECT

Some of this work was supported in part or in full by the BAA award.

• United States Genomic epidemiology identifies emergence and rapid transmission of SARS-CoV-2 B.1.1.7 in the United States , medRxiv , 2021.
• Emergence of an early SARS-CoV-2 epidemic in the United States, medRxiv , 2021.
• The ViReflow pipeline enables user-friendly large scale viral consensus genome reconstruction, Sci Rep , 2022.
• SARS-CoV-2 Distribution in Residential Housing Suggests Contact Deposition and Correlates with Rothia sp . mSystems , 2022.
• Wastewater sequencing uncovers early, cryptic SARS-CoV-2 variant transmission, Nature , 2022.
• Automated, miniaturized, and scalable screening of healthcare workers, first responders, and students forSARS-CoV-2 in San Diego County , medRxiv , 2021.
• Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations , medRxiv . 2021.
• Outbreak.info Research Library: A standardized, searchable platform to discover and explore COVID-19 resources, bioRxiv , 2022.
• The ViReflow pipeline enables user-friendly large scale viral consensus genome reconstruction. Sci Rep , 2022.

AMD integrates next-generation genomic sequencing technologies with bioinformatics and epidemiology expertise to help us find, track, and stop pathogens.

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Q&A: How did the COVID-19 pandemic affect older adults' technology use?

by Stefan Milne, University of Washington

The onset of the COVID-19 pandemic changed how nearly everyone mediated their social interactions through technology. Some moved happy hours into video chats. Others delved deeper into social media, or took a step back from it. Millions of people worked or learned through computers.

University of Washington researchers took particular interest in how this tech shift affected older adults' social relationships. The team interviewed 16 older adults in Washington and Oregon, ages 65 to 80, about how their technology use with their social support networks changed during the pandemic. Researchers found that these adults used technology both in their roles as recipients of support—such as a family member checking in on them—as well as providers of support—such as sending money to family members through apps like Zelle or PayPal.

The team published its findings April 26 in Proceedings of the ACM Conference on Computer-Supported Cooperative Work and Social Computing.

UW News spoke with lead author Shengzhi Wang, a UW doctoral student in human centered design and engineering, about the paper's findings.

Why did you study this?

Shengzhi Wang : The rapid adoption of technology we've seen in recent years has typically left older adults slightly behind. There is what's called a "gray divide," where older adults tend to be a bit later in adopting technologies like smartphones, tablets and smartwatches compared to younger demographics. But in recent years, we've seen quite a bit more adoption among older adults, and the pandemic spurred that on. Essentially, it forced a lot of people to start using these technologies out of necessity.

This paper looks at how technology affects the way older adults communicate with their social circle: people like family, friends, acquaintances or others that are a bit farther off in their networks, maybe their postal worker or people that they come across in the store once in a while. We were looking at what role technology plays in that circle.

What surprised you about the findings?

SW : The participants in our study were mostly able to overcome a lot of the technological and accessibility barriers that we've seen in past studies—for example, text that's too small. Those kinds of issues are definitely still around, but we found that these barriers didn't significantly affect the participants' willingness to use or adopt some of these services and technology.

We also found how much older adults were not only receivers of support but providers of it, whether that was emotional or financial or physical support. They were providing it for fellow older adults, as well as family members and friends.

Could you explain why understanding the dual role of supporter and supported is important when considering technology and how it's designed?

SW : Technologies we typically think of older adults using are for providing them with support. For example, you might have smart cameras for families to keep an eye on older adults or other things that let people check in on whether the older adult in their life is doing well. Those technologies definitely have their role. But we found that older adults tend to also have other needs when it comes to using technologies, especially in how they can provide support to others. Those uses aren't highlighted as much by technology designers and the people who are communicating about how technologies can be used.

What's an example of a technology that maybe isn't being used as much for that, but that already exists?

SW : In the study, we highlight technologies that try to replace in-person support experiences, such as an older adult having a coffee meeting with their friends. If you try to replace that with a Zoom meeting, which happened often, at least in the beginning of the pandemic, the closeness that they felt with their friends was extremely lacking. One participant described it as feeling like watching TV from afar. It was just not a great use of videoconferencing. The common belief was that this technology can replace in-person experiences, and that was definitely not how it worked out.

On the other hand, a lot of older adults really enjoyed telehealth for accessing mental health services. And that's basically the same technology. But they came in with the right expectations, and the technology provided something that they couldn't access in person. We also found people liking technology that supports in-person meetings and in-person activities, rather than trying to replace them. We saw a lot of people using text messaging or short video chats to plan in-person activities. In this case, we're not looking at technology and in-person as two completely separate things. When they work well together, they work really well together.

How could tech better serve older adults in their social connections?

SW : We highlight the need to codesign. Researchers and designers need to bring older adults into the design process of technology and take into account their individual circumstances, their social connections and how those affect technology use when they're both providing and receiving support.

This two-way communication is also important within families. We saw in some interviews that family members were really pushing older adults to start using some of these technologies, like social media or one way surveillance via smart cameras. From the family members' points of view, the older adults are missing out on some of the benefits of social media, like seeing photos or posts from families and friends or being provided with more safety. But sometimes older adults prefer in-person experiences, and they don't always like the privacy component of some technologies, for example. Technology should move away from enabling disempowering relationships or experiences for older adults.

What should the public know about this research?

SW : That older adults provide and receive social support is the most important piece. If you're thinking of buying technology for an older family member, you should really think about how it can play a part in that person's life. It might be a hindrance if it doesn't provide what they need. So it's really important to start that conversation early and respect their preferences.

Additional co-authors included Adoniah Carmeline, a regional design researcher at Daraz, who completed this work as a UW master's student; Beth Kolko and Sean Munson, both UW professors of human centered design and engineering. This work was supported by the National Science Foundation.

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Link between COVID-19 vaccine complication and rare ‘common cold’ blood disease

Flinders University

Flinders University immunology researchers Dr Jing Jing Wang and Professor Tom Gordon.

Credit: photo courtesy Flinders Foundation

New research led by Flinders University and international experts is expanding understanding of vaccine-induced immune thrombocytopenia and thrombosis (known as VITT).

At the height of the COVID-19 pandemic in 2021,VITT emerged as a new disease following adenovirus vector-based vaccines – notably the Oxford-AstraZeneca vaccine.

VITT was found to be caused by an unusually dangerous blood autoantibody directed against a protein termed platelet factor 4 (or PF4). 

In separate research in 2023, researchers from Canada, North America, Germany and Italy described a virtually identical disorder with the same PF4 antibody that was fatal in some cases after natural adenovirus (common cold) infection. 

Flinders University researchers Dr Jing Jing Wang and Flinders Professor Tom Gordon, Head of Immunology at SA Pathology in South Australia,  led a previous study  in 2022 which cracked the molecular code of the PF4 antibody and identified a genetic risk factor related to an antibody gene termed IGLV3.21*02. 

Now, the Flinders group has collaborated with this international group of researchers to find that the PF4 antibodies in both adenovirus infection-associated VITT and classic adenoviral vectored VITT share identical molecular fingerprints or signatures. 

The research will also have implications for improving vaccine development, says Flinders University researcher Dr Wang, first author on the new article to be published in the eminent  New England Journal of Medicine  on Thursday (embargoed 16 May 2024).

“These findings, using a completely new approach for targeting blood antibodies developed at Flinders University, indicate a common triggering factor on virus and vaccine structures that initiates the pathological pF4 antibodies,” explains Professor Gordon. 

"Indeed, the pathways of lethal antibody production in these disorders must be virtually identical and have similar genetic risk factors. 

"Our findings have the important clinical implication that lessons learned from VITT are applicable to rare cases of blood clotting after adenovirus (a common cold) infections, as well as having implications for vaccine development," he says.

Key points : 

• The anti-PF4 antibodies found in vaccine-induced immune thrombocytopenia and thrombosis (VITT) and in the adenovirus VITT-like disorder share essentially identical molecular signatures (or 'fingerprints’).
• The findings have important clinical implication that the lessons learned from VITT are applicable to adenovirus anti-PF4 disorders.
• The findings also have important implications for improving vaccine safety.

The original research letter, Correspondence entitled 'Antibody Fingerprints Linking Adenoviral Anti-PF4 Disorders' (2024), by Jing Jing Wang (Flinders University), Linda Schönborn (Greifswald University Hospital, Germany), Theodore E Warkentin (McMaster University, Canada), Tim Chataway (Flinders University), Leonie Grosse (Ludwig Maximilians University, Germany), Paolo Simioni (Padova University Hospital, Italy), Stephan Moll (University of North Carolina School of Medicine, US), Andreas Greinacher (Greifswald University Hospital, Germany) and Tom P Gordon (SA Pathology, South Australia) will be published in the  New England Journal of Medicine.  DOI: 10.1056/NEJMc2402592

Disclaimer:  The views expressed in this letter are those of the authors and do not necessarily represent the position of the European Medicines Agency.

Acknowledgements : The research was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft) and a European Medicines Agency service contract. Dr Schönborn was supported by the ASH Global Research Award from the American Society of Hematology and by the Gerhard Domagk Research Program through the Medical University of Greifswald. Dr Wang was supported by a Flinders Foundation Health Seed Grant.

New England Journal of Medicine

10.1056/NEJMc2402592

Method of Research

Observational study

Subject of Research

Article title.

Antibody Fingerprints Linking Adenoviral Anti-PF4 Disorders

Article Publication Date

16-May-2024

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

Global life expectancy to increase by nearly 5 years by 2050 despite geopolitical, metabolic, and environmental threats

The latest findings from the Global Burden of Disease Study (GBD) 2021, published today in The Lancet, forecast that global life expectancy will increase by 4.9 years in males and 4.2 years in females between 2022 and 2050.

Increases are expected to be largest in countries where life expectancy is lower, contributing to a convergence of increased life expectancy across geographies. The trend is largely driven by public health measures that have prevented and improved survival rates from cardiovascular diseases, COVID-19, and a range of communicable, maternal, neonatal, and nutritional diseases (CMNNs).

This study indicates that the ongoing shift in disease burden to non-communicable diseases (NCDs) -- like cardiovascular diseases, cancer, chronic obstructive pulmonary disease, and diabetes -- and exposure to NCD-associated risk factors -- such as obesity, high blood pressure, non-optimal diet, and smoking -- will have the greatest impact on disease burden of the next generation.

As the disease burden continues to shift from CMNNs to NCDs and from years of life lost (YLLs) to years lived with disability (YLDs), more people are expected to live longer, but with more years spent in poor health. Global life expectancy is forecasted to increase from 73.6 years of age in 2022 to 78.1 years of age in 2050 (a 4.5-year increase). Global healthy life expectancy (HALE) -- the average number of years a person can expect to live in good health -- will increase from 64.8 years in 2022 to 67.4 years in 2050 (a 2.6-year increase).

To come to these conclusions, the study forecasts cause-specific mortality; YLLs; YLDs; disability-adjusted life years (DALYs, or lost years of healthy life due to poor health and early death); life expectancy; and HALE from 2022 through 2050 for 204 countries and territories.

"In addition to an increase in life expectancy overall, we have found that the disparity in life expectancy across geographies will lessen," said Dr. Chris Murray, Chair of Health Metrics Sciences at the University of Washington and Director of the Institute for Health Metrics and Evaluation (IHME). "This is an indicator that while health inequalities between the highest- and lowest-income regions will remain, the gaps are shrinking, with the biggest increases anticipated in sub-Saharan Africa."

Dr. Murray added that the biggest opportunity to speed up reductions in the global disease burden is through policy interventions aimed to prevent and mitigate behavioral and metabolic risk factors.

These findings build upon the results of the GBD 2021 risk factors study, also released today in The Lancet . This accompanying study found that the total number of years lost due to poor health and early death (measured in DALYs) attributable to metabolic risk factors has increased by 50% since 2000. Read more on the risk factors report at https://bit.ly/GBDRisks2021 .

The study also puts forth various alternative scenarios to compare the potential health outcomes if different public health interventions could eliminate exposure to several key risk factor groups by 2050.

"We forecast large differences in global DALY burden between different alternative scenarios to see what is the most impactful on our overall life expectancy data and DALY forecasts," said Dr. Stein Emil Vollset, first author of the study who leads the GBD Collaborating Unit at the Norwegian Institute of Public Health. "Globally, the forecasted effects are strongest for the 'Improved Behavioral and Metabolic Risks' scenario, with a 13.3% reduction in disease burden (number of DALYs) in 2050 compared with the 'Reference' (most likely) scenario."

The authors also ran two more scenarios: one focused on safer environments and another on improved childhood nutrition and vaccination.

"Though the largest effects in global DALY burden were seen from the 'Improved Behavioral and Metabolic Risk' scenario, we also forecasted reductions in disease burden from the 'Safer Environment' and 'Improved Childhood Nutrition and Vaccination' scenarios beyond our reference forecast, said Amanda E. Smith, Assistant Director of Forecasting at IHME. "This demonstrates the need for continued progress and resources in these areas and the potential to accelerate progress through 2050."

"There is immense opportunity ahead for us to influence the future of global health by getting ahead of these rising metabolic and dietary risk factors, particularly those related to behavioral and lifestyle factors like high blood sugar, high body mass index, and high blood pressure," continued Dr. Murray.

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Story Source:

Materials provided by Institute for Health Metrics and Evaluation . Note: Content may be edited for style and length.

Journal Reference :

• Stein Emil Vollset et al. Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021 . The Lancet , 2024; 403 (10440): 2204 DOI: 10.1016/S0140-6736(24)00685-8

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