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Months After Recovery, COVID-19 Survivors Often Have Persistent Lung Trouble

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Lung function test
Caption: Testing breathing capacity with a spirometer. Credit: iStock/Koldunov

The pandemic has already claimed far too many lives in the United States and around the world. Fortunately, as doctors have gained more experience in treating coronavirus disease 2019 (COVID-19), more people who’ve been hospitalized eventually will recover. This raises an important question: what does recovery look like for them?

Because COVID-19 is still a new condition, there aren’t a lot of data out there yet to answer that question. But a recent study of 55 people recovering from COVID-19 in China offers some early insight into the recovery of lung function [1]. The results make clear that—even in those with a mild-to-moderate infection—the effects of COVID-19 can persist in the lungs for months. In fact, three months after leaving the hospital about 70 percent of those in the study continued to have abnormal lung scans, an indication that the lungs are still damaged and trying to heal.

The findings in EClinicalMedicine come from a team in Henan Province, China, led by Aiguo Xu, The First Affiliated Hospital of Zhengzhou University; Yanfeng Gao, Zhengzhou University; and Hong Luo, Guangshan People’s Hospital. They’d heard about reports of lung abnormalities in patients discharged from the hospital. But it wasn’t clear how long those problems stuck around.

To find out, the researchers enrolled 55 men and women who’d been admitted to the hospital with COVID-19 three months earlier. Some of the participants, whose average age was 48, had other health conditions, such as diabetes or heart disease. But none had any pre-existing lung problems.

Most of the patients had mild or moderate respiratory illness while hospitalized. Only four of the 55 had been classified as severely ill. Fourteen patients required supplemental oxygen while in the hospital, but none needed mechanical ventilation.

Three months after discharge from the hospital, all of the patients were able to return to work. But they continued to have lingering symptoms of COVID-19, including shortness of breath, cough, gastrointestinal problems, headache, or fatigue.

Evidence of this continued trouble also showed up in their lungs. Thirty-nine of the study’s participants had an abnormal result in their computed tomography (CT) lung scan, which creates cross-sectional images of the lungs. Fourteen individuals (1 in 4) also showed reduced lung function in breathing tests.

Interestingly, the researchers found that those who went on to have more lasting lung problems also had elevated levels of D-dimer, a protein fragment that arises when a blood clot dissolves. They suggest that a D-dimer test might help to identify those with COVID-19 who would benefit from pulmonary rehabilitation to rebuild their lung function, even in the absence of severe respiratory symptoms.

This finding also points to the way in which the SARS-CoV-2 virus seems to enhance a tendency toward blood clotting—a problem addressed in our Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) public-private partnership. The partnership recently initiated a trial of blood thinners. That trial will start out by focusing on newly diagnosed outpatients and hospitalized patients, but will go on to include a component related to convalescence.

Moving forward, it will be important to conduct larger and longer-term studies of COVID-19 recovery in people of diverse backgrounds to continue to learn more about what it means to survive COVID-19. The new findings certainly indicate that for many people who’ve been hospitalized with COVID-19, regaining normal lung function may take a while. As we learn even more about the underlying causes and long-term consequences of this new infectious disease, let’s hope it will soon lead to insights that will help many more COVID-19 long-haulers and their concerned loved ones breathe easier.

Reference:

[1] Follow-up study of the pulmonary function and related physiological characteristics of COVID-19 survivors three months after recovery. Zhao YM, Shang YM, Song WB, Li QQ, Xie H, Xu QF, Jia JL, Li LM, Mao HL, Zhou XM, Luo H, Gao YF, Xu AG. EClinicalMedicine.2020 Aug 25:100463

Links:

Coronavirus (COVID-19) (NIH)

How the Lungs Work (National Heart, Lung, and Blood Institute/NIH)

Computed Tomography (CT) (National Institute of Biomedical Imaging and Bioengineering/NIH)

Zhengzhou University (Zhengzhou City, Henan Province, China)

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) (NIH)


Genome Data Help to Track COVID-19 Superspreading Event

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Boston skyline
Credit: iStock/Chaay_Tee

When it comes to COVID-19, anyone, even without symptoms, can be a “superspreader” capable of unknowingly infecting a large number of people and causing a community outbreak. That’s why it is so important right now to wear masks when out in public and avoid large gatherings, especially those held indoors, where a superspreader can readily infect others with SARS-CoV-2, the virus responsible for COVID-19.

Driving home this point is a new NIH-funded study on the effects of just one superspreader event in the Boston area: an international biotech conference held in February, before the public health risks of COVID-19 had been fully realized [1]. Almost a hundred people were infected. But it didn’t end there.

In the study, the researchers sequenced close to 800 viral genomes, including cases from across the first wave of the epidemic in the Boston area. Using the fact that the viral genome changes in very subtle ways over time, they found that SARS-CoV-2 was actually introduced independently to the region more than 80 times, primarily from Europe and other parts of the United States. But the data also suggest that a single superspreading event at the biotech conference led to the infection of almost 20,000 people in the area, not to mention additional COVID-19 cases in other states and around the world.

The findings, posted on medRxiv as a pre-print, come from Bronwyn MacInnis and Pardis Sabeti at the Broad Institute of MIT and Harvard in Cambridge, MA, and their many close colleagues at Massachusetts General Hospital, the Massachusetts Department of Public Health, and the Boston Health Care for the Homeless Program. The initial focus of MacInnis, Sabeti, and their Broad colleagues has been on developing genome data and tools for surveillance of viruses and other infectious diseases in and viral outbreaks in West Africa, including Lassa fever and Ebola virus disease.

Closer to home, they’d expected to focus their attention on West Nile virus and tick-borne diseases. But, when the COVID-19 outbreak erupted, they were ready to pivot quickly to assist several Centers for Disease Control and Prevention (CDC) and state labs in the northeastern United States to use genomic tools to investigate local outbreaks.

It’s been clear from the beginning of the pandemic that COVID-19 cases often arise in clusters, linked to gatherings in places such as cruise ships, nursing homes, and homeless shelters. But the Broad Institute team and their colleagues realized, it’s difficult to see how extensively a virus spreads from such places into the wider community based on case counts alone.

Contact tracing certainly helps to track community spread of the virus. This surveillance strategy depends on quick, efficient identification of an infected individual. It follows up with the identification of all who’ve recently been in close contact with that person, allowing the contacts to self-quarantine and break the chain of transmission.

But contact tracing has its limitations. It’s not always possible to identify all the people that an infected person has been in recent contact with. Genome data, however, is particularly useful after the fact for connecting those dots to get a big picture view of viral transmission.

Here’s how it works: as SARS-CoV-2 spreads, the virus sometimes picks up a new mutation. Those tiny spelling changes in the viral genome usually have no effect on how the virus causes disease, but they do serve as distinct genomic fingerprints. Using those fingerprints to guide the way, researchers can trace the path the virus took through a community and beyond, identifying connections among cases that would be untrackable otherwise.

With this in mind, MacInnis and Sabeti’s team set out to help Boston’s public health officials understand just how the epidemic escalated so quickly in the Boston area, and just how much the February conference had contributed to community transmission of the virus. They also investigated other case clusters in the area, including within a skilled nursing facility, homeless shelters, and at Massachusetts General Hospital itself, to understand the spread of COVID-19 in these settings.

Based on contact tracing, officials had already connected approximately 90 cases of COVID-19 to the biotech conference, 28 of which were included in the original 772 viral genomes in this dataset. Based on the distinct genomic fingerprint carried by the 28 genomes, the researchers went on to discover that more than one-third of Boston area cases without any known link to the conference could indeed be traced back to the event.

When the researchers considered this proportion to the number of cases recorded in the region during the study, they extrapolated that the superspreader event led to nearly 20,000 cases in the Boston area. In contrast, the genome data show cases linked to another superspreader event that took place within a skilled nursing facility, while devastating to the residents, had much less of an impact on the surrounding community.

The analysis also uncovered some unexpected connections. The dataset showed that SARS-CoV-2 was brought to clients and staff at the Boston Health Care for the Homeless Program at least seven times. Remarkably, two of those introductions also traced back to the biotech conference. Researchers also found infections in Chelsea, Revere, and Everett, which were some of the hardest hit communities in the Boston area, that were connected to the original superspreading event.

There was some reassuring news about how precautions in hospitals are working. The researchers examined cases that were diagnosed among patients at Massachusetts General Hospital, raising concerns that the virus might have spread from one patient to another within the hospital. But the genome data show that those cases, in fact, weren’t part of the same transmission chain. They may have contracted the virus before they were hospitalized. Or it’s possible that staff may have inadvertently brought the virus into the hospital. But there was no patient-to-patient transmission.

Massachusetts is one of the states in which the COVID-19 pandemic had a particularly severe early impact. As such, these results present broadly applicable lessons for other states and urban areas about how the virus spreads. The findings highlight the value of genomic surveillance, along with standard contact tracing, for better understanding of viral transmission in our communities and improved prevention of future outbreaks.

Reference:

[1] Phylogenetic analysis of SARS-CoV-2 in the Boston area highlights the role of recurrent importation and superspreading events. Lemieux J. et al. medRxiv. August 25, 2020.

Links:

Coronavirus (COVID-19) (NIH)

Bronwyn MacInnis (Broad Institute of Harvard and MIT, Cambridge, MA)

Sabeti Lab (Broad Institute of Harvard and MIT)

NIH Support: National Institute of Allergy and Infectious Diseases; National Human Genome Research Institute; National Institute of General Medical Sciences


Citizen Scientists Take on the Challenge of Long-Haul COVID-19

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Woman frustrated while working
Credit: iStock/Poike

Coronaviruses are a frequent cause of the common cold. Most of us bounce back from colds without any lasting health effects. So, you might think that individuals who survive other infectious diseases caused by coronaviruses—including COVID-19—would also return to normal relatively quickly. While that can be the case for some people, others who’ve survived even relatively mild COVID-19 are experiencing health challenges that may last for weeks or even months. In fact, the situation is so common, that some of these folks have banded together and given their condition a name: the COVID “long-haulers.”

Among the many longer-term health problems that have been associated with COVID-19 are shortness of breath, fatigue, cognitive issues, erratic heartbeat, gastrointestinal issues, low-grade fever, intolerance to physical or mental activity, and muscle and joint pains. COVID-19 survivors report that these symptoms flair up unpredictably, often in different combinations, and can be debilitating for days and weeks at a time. Because COVID-19 is such a new disease, little is known about what causes the persistence of symptoms, what is impeding full recovery, or how to help the long-haulers.

More information is now emerging from the first detailed patient survey of post-COVID syndrome, also known as Long COVID [1]. What’s unique about the survey is that it has been issued by a group of individuals who are struggling with the syndrome themselves. These citizen scientists, who belong to the online Body Politic COVID-19 Support Group, decided to take matters into their own hands. They already had a pretty good grip on what sort of questions to ask, as well as online access to hundreds of long-haulers to whom they could pose the questions.

The citizen scientists’ group, known as the Patient-led Research for COVID-19, brought a lot of talent and creativity to the table. Members reside in the United States, Canada, and England, and none have ever met face to face. But, between their day jobs, managing time differences, and health challenges, each team member spends about 20 hours per week working on their patient-led research, and are now putting the final touches on a follow-up survey that will get underway in the next few weeks.

For their first survey, the group members faced the difficult decision of whom to contact. First, they needed to define long hauler. For that, they decided to target people whose symptoms persisted for more than 2 weeks after their initial recovery from COVID-19. The 640 individuals who responded to the survey were predominately white females between the ages of 30 to 49 who lived in the United States. The members said that the gender bias may stem from women being more likely to join support groups and complete surveys, though there may be a gender component to Long COVID as well. About 10 percent of respondents reported that they had ultimately recovered from this post-COVID syndrome.

Another important issue revolved around COVID-19 testing. Most long-haulers in the online group had gotten sick in March and April, but weren’t so sick that they needed to be hospitalized. Because COVID-19 testing during those months was often limited to people hospitalized with severe respiratory problems, many long-haulers with mild or moderate COVID-like symptoms weren’t tested. Others were tested relatively late in the course of their illness, which can increase the likelihood of false negatives.

The team opted to cast a wide investigative net, concluding that limiting its data to only people who tested positive for COVID-19 might lead to the loss of essential information on long-haulers. It turns out that half of the respondents hadn’t been tested for SARS-CoV-2, the virus that causes COVID-19. The other half was divided almost equally between those who tested positive and those who tested negative. Here are some highlights of the survey’s findings:

Top 10 Symptoms: Respondents were asked to rank their most common symptoms and their relative severity. From highest to lowest, they were: mild shortness of breath, mild tightness of chest, moderate fatigue, mild fatigue, chills or sweats, mild body aches, dry cough, elevated temperature (98.8-100), mild headache, and brain fog/concentration challenges. Highlighting the value of patient-led research, the team was able to assemble an initial list of 62 symptoms that long-haulers often discuss in support groups. The survey revealed common symptoms that have been greatly underreported in the media, such as neurological symptoms. These include brain fog, concentration challenges, and dizziness.

Making a Recovery: Of the 60 respondents who had recovered, the average time to recovery was 27 days. The respondents who had not recovered had managed their symptoms for 40 days on average, with most dealing with health problems for 5 to 7 weeks. The report shows that the chance of full recovery by day 50 is less than 20 percent.

Exercise Capacity: About 65 percent of respondents now consider themselves mostly sedentary. Most had been highly physically active before developing COVID-19. Many long-haulers expressed concern that overexertion causes relapses

Testing. Respondents who reported testing positive for SARS-CoV-2 were tested on average earlier in their illness (by day 10) than those who reported testing negative (by day 16). The team noted that their findings parallel those in a recent published scientific study, which found false-negative rates for current PCR-based assays rose as the time between SARS-CoV-2 infection and testing increased [2]. In that published study, by day 21, the false-negative rate reached 66 percent. Only two symptoms (loss of smell and loss of taste) occurred more frequently in respondents who tested positive; the other 60 symptoms were statistically the same between groups. The citizen scientists speculate that testing is not capturing a subset of COVID patients, and more investigation is required.

Since issuing their survey results on May 11, the team has met with staff from the Centers for Disease Control and Prevention and the World Health Organization. Their work also been mentioned in magazine articles and even cited in some papers published in scientific journals.

In their next survey, these citizen scientists hope to fill in gaps in their first report, including examining antibody testing results, neurological symptoms, and the role of mental health. To increase geographic and demographic diversity, they will also translate the survey into 10 languages. If you’re a COVID-19 long-hauler and would like to find out how to get involved, there’s still time to take part in the next survey.

References:

[1] “What Does COVID-19 Recovery Actually Look Like?” Patient-led Research for COVID-19. May 11, 2020.

[2] Variation in False-Negative Rate of Reverse Transcriptase Polymerase Chain Reaction-Based SARS-CoV-2 Tests by Time Since Exposure. Kucirka LM, Lauer SA, Laeyendecker O, Boon D, Lessler J. Ann Intern Med. 2020 Aug 18;173(4):262-267.

Links:

Coronavirus (COVID-19) (NIH)

Patient-led Research for COVID-19


Study Ties COVID-19-Related Syndrome in Kids to Altered Immune System

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Very sick child
Credit: iStock/Sasiistock

Most children infected with SARS-CoV-2, the virus that causes COVID-19, develop only a mild illness. But, days or weeks later, a small percentage of kids go on to develop a puzzling syndrome known as multisystem inflammatory syndrome in children (MIS-C). This severe inflammation of organs and tissues can affect the heart, lungs, kidneys, brain, skin, and eyes.

Thankfully, most kids with MIS-C respond to treatment and make rapid recoveries. But, tragically, MIS-C can sometimes be fatal.

With COVID-19 cases in children having increased by 21 percent in the United States since early August [2], NIH and others are continuing to work hard on getting a handle on this poorly understood complication. Many think that MIS-C isn’t a direct result of the virus, but seems more likely to be due to an intense autoimmune response. Indeed, a recent study in Nature Medicine [1] offers some of the first evidence that MIS-C is connected to specific changes in the immune system that, for reasons that remain mysterious, sometimes follow COVID-19.

These findings come from Shane Tibby, a researcher at Evelina London Children’s Hospital, London. United Kingdom; Manu Shankar-Hari, a scientist at Guy’s and St Thomas’ NHS Foundation Trust, London; and colleagues. The researchers enlisted 25 children, ages 7 to 14, who developed MIS-C in connection with COVID-19. In search of clues, they examined blood samples collected from the children during different stages of their care, starting when they were most ill through recovery and follow-up. They then compared the samples to those of healthy children of the same ages.

What they found was a complex array of immune disruptions. The children had increased levels of various inflammatory molecules known as cytokines, alongside raised levels of other markers suggesting tissue damage—such as troponin, which indicates heart muscle injury.

The neutrophils, monocytes, and other white blood cells that rapidly respond to infections were activated as expected. But the levels of certain white blood cells called T lymphocytes were paradoxically reduced. Interestingly, despite the low overall numbers of T lymphocytes, particular subsets of them appeared activated as though fighting an infection. While the children recovered, those differences gradually disappeared as the immune system returned to normal.

It has been noted that MIS-C bears some resemblance to an inflammatory condition known as Kawasaki disease, which also primarily affects children. While there are similarities, this new work shows that MIS-C is a distinct illness associated with COVID-19. In fact, only two children in the study met the full criteria for Kawasaki disease based on the clinical features and symptoms of their illness.

Another recent study from the United Kingdom, reported several new symptoms of MIS-C [3]. They include headaches, tiredness, muscle aches, and sore throat. Researchers also determined that the number of platelets was much lower in the blood of children with MIS-C than in those without the condition. They proposed that evaluating a child’s symptoms along with his or her platelet level could help to diagnose MIS-C.

It will now be important to learn much more about the precise mechanisms underlying these observed changes in the immune system and how best to treat or prevent them. In support of this effort, NIH recently announced $20 million in research funding dedicated to the development of approaches that identify children at high risk for developing MIS-C [4].

The hope is that this new NIH effort, along with other continued efforts around the world, will elucidate the factors influencing the likelihood that a child with COVID-19 will develop MIS-C. Such insights are essential to allow doctors to intervene as early as possible and improve outcomes for this potentially serious condition.

References:

[1] Peripheral immunophenotypes in children with multisystem inflammatory syndrome associated with SARS-CoV-2 infection. Carter MJ, Fish M, Jennings A, Doores KJ, Wellman P, Seow J, Acors S, Graham C, Timms E, Kenny J, Neil S, Malim MH, Tibby SM, Shankar-Hari M. Nat Med. 2020 Aug 18.

[2] Children and COVID-19: State-Level Data Report. American Academy of Pediatrics. August 24, 2020.

[3] Clinical characteristics of children and young people admitted to hospital with covid-19 in United Kingdom: prospective multicentre observational cohort study. Swann OV, Holden KA, Turtle L, Harrison EW, Docherty AB, Semple MG, et al. Br Med J. 2020 Aug 17.

[4] NIH-funded project seeks to identify children at risk for MIS-C. NIH. August 7, 2020.

Links:

Coronavirus (COVID-19) (NIH)

Kawasaki Disease (Genetic and Rare Disease Information Center/National Center for Advancing Translational Sciences/NIH)

Shane Tibby (Evelina London Children’s Hospital, London)

Manu Shankar-Hari (King’s College, London)

NIH Support: Eunice Kennedy Shriver National Institute of Child Health and Human Development; Office of the Director; National Heart, Lung, and Blood Institute; National Institute of Allergy and Infectious Diseases; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute on Drug Abuse; National Institute of Minority Health and Health Disparities; Fogarty International Center


Masks Save Lives

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Masks save lives

Reminding others that “masks save lives” isn’t just sound advice. It’s a scientific fact that wearing one in public can help to slow the spread of SARS-CoV-2, the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic.

I’m very careful to wear a mask outside my home whenever I’m out and about. I do it not necessarily to protect myself, but to protect others. If by chance I’ve been exposed to the virus and am currently incubating it, I wouldn’t want to spread it to other people. And any of us could be an unknowing superspreader. We owe it to everyone we encounter, especially those who are more vulnerable, to protect them. As my NIH colleague Tony Fauci recently demonstrated, it’s possible to wear your mask even while you’re outside exercising.

But there are still skeptics around. So, just how much does a facial covering protect those around you? Quite a bit, according to researchers who created a sophisticated mathematical model to take a more detailed look [1]. Their model shows that even if a community universally adopted a crude cloth covering that’s far less than 100 percent protective against the virus, this measure alone could significantly help to reduce deaths.

These findings, funded partly by NIH, were published recently in Nature Communications. They come from Colin Worby, Broad Institute of MIT and Harvard, Cambridge, MA, and Hsiao-Han Chang, National Tsing Hua University, Taiwan.

The researchers noted several months ago that recommendations on wearing a mask varied across the United States and around the world. To help guide policymakers, the researchers simulated outbreaks in a closed, randomly interacting population in which the supply and effectiveness of crude cloth or disposable, medical-grade masks varied.

Under different outbreak scenarios and mask usages, the researchers calculated the total numbers of expected SARS-CoV-2 infections and deaths from COVID-19. Not surprisingly, they found that the total number of deaths and infections declined as the availability and effectiveness of face masks increased.

The researchers’ model primarily considered the distribution of medical-grade, surgical masks. But because such masks are currently available in limited supply, they must be prioritized for use by health care workers and others at high risk. The researchers go on to note that the World Health Organization and others now recommend wearing homemade face coverings in public, especially in places where the virus is spreading. While it’s true the ability of these face coverings to contain the virus is more limited than medical-grade masks, they can help and will lead to many fewer deaths.

Another recent paper also suggests that while wearing a mask is primarily intended to prevent the wearer from infecting others, it may also help lower the dose, or inoculum, of SARS-CoV-2 that the wearer might receive from others, resulting in milder or asymptomatic infections [2]. If correct, that’s another great reason to wear a mask.

Already, more than 175,000 people in the United States have died from COVID-19. The latest estimates [3] from the Institute for Health Metrics and Evaluation (IHME) at the University of Washington’s School of Medicine, Seattle, predict that the COVID-19 death toll in the U.S. may reach nearly 300,000 by December 1.

But that doesn’t have to happen. As this new study shows, face coverings—even those that are far from perfect—really can and do save lives. In fact, IHME data also show that consistent mask-wearing—starting today—could save close to 70,000 lives in the months to come. Saving those lives is up to all of us. Don’t leave home without your mask.

References:

[1] Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic. Worby CJ, Chang HH. Nat Commun. 2020 Aug 13;11(1):4049.

[2] Masks Do More Than Protect Others During COVID-19: Reducing the Inoculum of SARS-CoV-2 to Protect the Wearer. Gandhi M, Beyrer C, Goosby E. J Gen Intern Med. 2020 Jul 31.

[3] New IHME COVID-19 forecasts see nearly 300,000 deaths by December 1. Institute for Health Metrics and Evaluation. August 6, 2020.

Links:

Coronavirus (COVID-19) (NIH)

Colin Worby (Broad Institute of MIT and Harvard, Cambridge, MA)

Hsiao-Han Chang (National Tsing Hua University, Taiwan)

NIH Support: National Institute of Allergy and Infectious Diseases


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