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Public Health Policies Have Prevented Hundreds of Millions of Coronavirus Infections

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Credit: Stock photo/Juanmonino

The alarming spread of coronavirus disease 2019 (COVID-19) last winter presented a profound threat to nations around the world. Many government leaders responded by shutting down all non-essential activities, implementing policies that public health officials were hopeful could slow the highly infectious SARS-CoV-2, the novel coronavirus that causes COVID-19.

But the shutdown has come at a heavy cost for the U.S. and global economies. It’s also taken a heavy personal toll on many of us, disrupting our daily routines—getting children off to school, commuting to the office or lab, getting together with friends and family, meeting face to face to plan projects, eating out, going to the gym—and causing lots of uncertainty and frustration.

As difficult as the shutdowns have been, new research shows that without these public health measures, things would have been much, much worse. According to a study published recently in Nature [1], the implementation of containment and mitigation strategies across the globe prevented or delayed about 530 million coronavirus infections across six countries—China, South Korea, Iran, Italy, France, and the United States. Take a moment to absorb that number—530 million. Right now, there are 8.8 million cases documented across the globe.

Estimates of the benefits of anti-contagion policies have drawn from epidemiological models that simulate the spread of COVID-19 in various ways, depending on assumptions built into each model. But models are sophisticated ways of guessing. Back when decisions about staying at home had to be made, no one knew for sure if, or how well, such approaches to limit physical contact would work. What’s more, the only real historical precedent was the 1918 Spanish flu pandemic in a very different, much-less interconnected world.

That made it essential to evaluate the pros and cons of these public health strategies within a society. As many people have rightfully asked: are the health benefits really worth the pain?

Recognizing a pressing need to answer this question, an international team of scientists dropped everything that they were doing to find out. Led by Solomon Hsiang, director of the University of California, Berkeley’s Global Policy Laboratory and Chancellor’s Professor at the Goldman School of Public Policy, a research group of 15 researchers from China, France, South Korea, New Zealand, Singapore, and the United States evaluated 1,717 policies implemented in all six countries between January 2020, when the virus began its global rise, and April 6, 2020.

The team relied on econometric methods that use statistics and math to uncover meaningful patterns hiding in mountains of data. As the name implies, these techniques are used routinely by economists to understand, in a before-and-after way, how certain events affect economic growth.

In this look-back study, scientists compare observations before and after an event they couldn’t control, such as a natural disaster or disease outbreak. In the case of COVID-19, these researchers compared public health datasets in multiple localities (e.g., states or cities) within each of the six countries before and several weeks after lockdowns. For each data sample from a given locality, the time period right before a policy deployment was the experimental “control” for the same locality several weeks after it received one or more shutdown policy “treatments.”

Hsiang and his colleagues measured the effects of all the different policies put into place at local, regional, and national levels. These included travel restrictions, business and school closures, shelter-in-place orders, and other actions that didn’t involve any type of medical treatment for COVID-19.

Because SARS-CoV-2 is a new virus, the researchers knew that early in the pandemic, everyone was susceptible, and the outbreak would grow exponentially. The scientists could then use a statistical method designed to estimate how the daily growth rate of infections changed over time within a location after different combinations of large-scale policies were put into place.

The result? Early in the pandemic, coronavirus infection rates grew 38 percent each day, on average, across the six countries: translating to a two-day doubling time. Applying all policies at once slowed the daily COVID-19 infection rate by 31 percentage points! Policies having the clearest benefit were business closures and lockdowns, whereas travel restrictions and bans on social gatherings had mixed results. Without more data, the analysis can’t specify why, but the way different countries enacted those policies might be one reason.

As we continue to try to understand and thwart this new virus and its damage to so many aspects of our personal and professional lives, these new findings add context, comfort, and guidance about the present circumstances. They tell us that individual sacrifices from staying home and canceled events contributed collectively to a huge, positive impact on the world.

Now, as various communities start cautiously to open up, we should continue to practice social distancing, mask wearing, and handwashing. This is not the time to say that the risk has passed. We are all tired of the virus and its consequences for our personal lives, but the virus doesn’t care. It’s still out there. Stay safe, everyone!

Reference:

[1] The effect of large-scale anti-contagion policies on the COVID-19 pandemic. Hsiang S, Allen D, Annan-Phan S, et al. Nature. 2020 June 8 [published online ahead of print].

Links:

Coronavirus (NIH)

Global Policy Lab: Effect of Anti-Contagion Policies (University of California, Berkeley)

Video: How much have policies to slow COVID-19 worked? (UC Berkeley)

Hsiang Lab (UC Berkeley)

Global Policy Lab Rallies for COVID-19 Research,” COVID-19 News, Goldman School of Public Policy, June 5, 2020.


First Molecular Profiles of Severe COVID-19 Infections

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COVID-19 Severity Test
Credit: NIH

To ensure that people with coronavirus disease 2019 (COVID-19) get the care they need, it would help if a simple blood test could predict early on which patients are most likely to progress to severe and life-threatening illness—and which are more likely to recover without much need for medical intervention. Now, researchers have provided some of the first evidence that such a test might be possible.

This tantalizing possibility comes from a study reported recently in the journal Cell. In this study, researchers took blood samples from people with mild to severe COVID-19 and analyzed them for nearly 2,000 proteins and metabolites [1]. Their detailed analyses turned up hundreds of molecular changes in blood that differentiated milder COVID-19 symptoms from more severe illness. What’s more, they found that they could train a computer to use the most informative of the proteins and predict the disease severity with a high degree of accuracy.

The findings come from the lab of Tiannan Guo, Westlake University, Zhejiang Province, China. His team recognized that, while we’ve learned a lot about the clinical symptoms of COVID-19 and the spread of the illness around the world, much less is known about the condition’s underlying molecular features. It also remains mysterious what distinguishes the 80 percent of symptomatic infected people who recover with little to no need for medical care from the other 20 percent, who suffer from much more serious illness, including respiratory distress requiring oxygen or even more significant medical interventions.

In search of clues, Guo and colleagues analyzed hundreds of molecular changes in blood samples collected from 53 healthy people and 46 people with COVID-19, including 21 with severe disease involving respiratory distress and decreased blood-oxygen levels. Their studies turned up more than 470 proteins and metabolites that differed in people with COVID-19 compared to healthy people. Of those, levels of about 300 were associated with disease severity.

Further analysis revealed that the majority of proteins and metabolites on the list are associated with the suppression or dysregulation of one of three biological processes. Two processes are related to the immune system, including early immune responses and the function of particular scavenging immune cells called macrophages. The third relates to the function of platelets, which are sticky, disc-shaped cell fragments that play an essential role in blood clotting. Such biological insights might help pave the way for potentially effective new ways to treat COVID-19 down the road.

Next, the researchers turned to “machine learning” to explore the possibility that such molecular changes also might be used to predict mild versus severe COVID-19. Machine learning involves the use of computers to discern patterns, or molecular signatures, in large data sets that a human being couldn’t readily pick out. In this case, the question was whether the computer could “learn” to tell the difference between mild and severe COVID-19 based on molecular data alone.

Their analyses showed that a computer, once trained, could differentiate mild and severe COVID-19 based on just 22 proteins and 7 metabolites. Their model correctly classified all but one person in the original training set, for an accuracy of about 94 percent. And importantly, in further prospective validation tests, they confirmed that this model accurately identified mild versus severe COVID-19 in most cases.

While these findings are certainly encouraging, there’s much more work to do. It will be important to explore these molecular signatures in many more people. It also will be critical to find out how early in the course of the disease such telltale signatures arise. While we await those answers, I find encouragement in all that we’re learning—and will continue to learn—about COVID-19 each day.

Reference:

[1] Proteomic and metabolomic characterization of COVID-19 patient sera. Shen B et al. Cell. 28 May 2020. [Epub ahead of publication]

Links:

Coronavirus (COVID-19) (NIH)

Blood Tests (National Heart, Lung, and Blood Institute/NIH)

Tiannan Guo Lab (Westlake University, Zhejiang Province, China)


Enlisting Monoclonal Antibodies in the Fight Against COVID-19

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B38 Antibody and SARS-CoV-2 wtih ACE2 Receptor
Caption: Antibody Binding to SARS-CoV-2. Structural illustration of B38 antibody (cyan, green) attached to receptor-binding domain of the coronavirus SARS-CoV-2 (magenta). B38 blocks SARS-CoV-2 from binding to the ACE2 receptor (light pink) of a human cell, ACE2 is what the virus uses to infect cells. Credit: Y. Wu et a. Science, 2020

We now know that the immune system of nearly everyone who recovers from COVID-19 produces antibodies against SARS-CoV-2, the novel coronavirus that causes this easily transmitted respiratory disease [1]. The presence of such antibodies has spurred hope that people exposed to SARS-CoV-2 may be protected, at least for a time, from getting COVID-19 again. But, in this post, I want to examine another potential use of antibodies: their promise for being developed as therapeutics for people who are sick with COVID-19.

In a recent paper in the journal Science, researchers used blood drawn from a COVID-19 survivor to identify a pair of previously unknown antibodies that specifically block SARS-CoV-2 from attaching to human cells [2]. Because each antibody locks onto a slightly different place on SARS-CoV-2, the vision is to use these antibodies in combination to block the virus from entering cells, thereby curbing COVID-19’s destructive spread throughout the lungs and other parts of the body.

The research team, led by Yan Wu, Capital Medical University, Beijing, first isolated the pair of antibodies in the laboratory, starting with white blood cells from the patient. They were then able to produce many identical copies of each antibody, referred to as monoclonal antibodies. Next, these monoclonal antibodies were simultaneously infused into a mouse model that had been infected with SARS-CoV-2. Just one infusion of this combination antibody therapy lowered the amount of viral genetic material in the animals’ lungs by as much as 30 percent compared to the amount in untreated animals.

Monoclonal antibodies are currently used to treat a variety of conditions, including asthma, cancer, Crohn’s disease, and rheumatoid arthritis. One advantage of this class of therapeutics is that the timelines for their development, testing, and approval are typically shorter than those for drugs made of chemical compounds, called small molecules. Because of these and other factors, many experts think antibody-based therapies may offer one of the best near-term options for developing safe, effective treatments for COVID-19.

So, what exactly led up to this latest scientific achievement? The researchers started out with a snippet of SARS-CoV-2’s receptor binding domain (RBD), a vital part of the spike protein that protrudes from the virus’s surface and serves to dock the virus onto an ACE2 receptor on a human cell. In laboratory experiments, the researchers used the RBD snippet as “bait” to attract antibody-producing B cells in a blood sample obtained from the COVID-19 survivor. Altogether, the researchers identified four unique antibodies, but two, which they called B38 and H4, displayed a synergistic action in binding to the RBD that made them stand out for purposes of therapeutic development and further testing.

To complement their lab and animal experiments, the researchers used a particle accelerator called a synchrotron to map, at near-atomic resolution, the way in which the B38 antibody locks onto its viral target. This structural information helps to clarify the precise biochemistry of the complex interaction between SARS-CoV-2 and the antibody, providing a much-needed guide for the rational design of targeted drugs and vaccines. While more research is needed before this or other monoclonal antibody therapies can be used in humans suffering from COVID-19, the new work represents yet another example of how basic science is expanding fundamental knowledge to advance therapeutic discovery for a wide range of health concerns.

Meanwhile, there’s been other impressive recent progress towards the development of monoclonal antibody therapies for COVID-19. In work described in the journal Nature, an international research team started with a set of neutralizing antibodies previously identified in a blood sample from a person who’d recovered from a different coronavirus-caused disease, called severe acute respiratory syndrome (SARS), in 2003 [3]. Through laboratory and structural imaging studies, the researchers found that one of these antibodies, called S309, proved particularly effective at neutralizing the coronavirus that causes COVID-19, SARS-CoV-2, because of its potent ability to target the spike protein that enables the virus to enter cells. The team, which includes NIH grantees David Veesler, University of Washington, Seattle, and Davide Corti, Humabs Biomed, a subsidiary of Vir Biotechnology, has indicated that S309 is already on an accelerated development path toward clinical trials.

In the U.S. and Europe, the Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) partnership, which has brought together public and private sector COVID-19 therapeutic and vaccine efforts, is intensely pursuing the development and testing of therapeutic monoclonal antibodies for COVID-19 [4]. Stay tuned for more information about these potentially significant advances in the next few months.

References:

[1] Humoral immune response and prolonged PCR positivity in a cohort of 1343 SARS-CoV 2 patients in the New York City region. Wajnberg A , Mansour M, Leven E, Bouvier NM, Patel G, Firpo A, Mendu R, Jhang J, Arinsburg S, Gitman M, Houldsworth J, Baine I, Simon V, Aberg J, Krammer F, Reich D, Cordon-Cardo C. medRxiv. Preprint Posted May 5, 2020.

[2] A noncompeting pair of human neutralizing antibodies block COVID-19 virus binding to its receptor ACE2. Wu Y. et al., Science. 13 May 2020 [Epub ahead of publication]

[3] Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV antibody. Pinto D, Park YJ, Beltramello M, Veesler D, Cortil D, et al. Nature. 18 May 2020 [Epub ahead of print]

[4] Accelerating COVID-19 therapeutic interventions and vaccines (ACTIV): An unprecedented partnership for unprecedented times. Collins FS, Stoffels P. JAMA. 2020 May 18.

Links:

Coronavirus (COVID-19) (NIH)

Monoclonal Antibodies (National Cancer Institute/NIH)

Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV)

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


Study Finds Nearly Everyone Who Recovers From COVID-19 Makes Coronavirus Antibodies

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Credit: NIH

There’s been a lot of excitement about the potential of antibody-based blood tests, also known as serology tests, to help contain the coronavirus disease 2019 (COVID-19) pandemic. There’s also an awareness that more research is needed to determine when—or even if—people infected with SARS-CoV-2, the novel coronavirus that causes COVID-19, produce antibodies that may protect them from re-infection.

A recent study in Nature Medicine brings much-needed clarity, along with renewed enthusiasm, to efforts to develop and implement widescale antibody testing for SARS-CoV-2 [1]. Antibodies are blood proteins produced by the immune system to fight foreign invaders like viruses, and may help to ward off future attacks by those same invaders.

In their study of blood drawn from 285 people hospitalized with severe COVID-19, researchers in China, led by Ai-Long Huang, Chongqing Medical University, found that all had developed SARS-CoV-2 specific antibodies within two to three weeks of their first symptoms. Although more follow-up work is needed to determine just how protective these antibodies are and for how long, these findings suggest that the immune systems of people who survive COVID-19 have been be primed to recognize SARS-CoV-2 and possibly thwart a second infection.

Specifically, the researchers determined that nearly all of the 285 patients studied produced a type of antibody called IgM, which is the first antibody that the body makes when fighting an infection. Though only about 40 percent produced IgM in the first week after onset of COVID-19, that number increased steadily to almost 95 percent two weeks later. All of these patients also produced a type of antibody called IgG. While IgG often appears a little later after acute infection, it has the potential to confer sustained immunity.

To confirm their results, the researchers turned to another group of 69 people diagnosed with COVID-19. The researchers collected blood samples from each person upon admission to the hospital and every three days thereafter until discharge. The team found that, with the exception of one woman and her daughter, the patients produced specific antibodies against SARS-CoV-2 within 20 days of their first symptoms of COVID-19.

Meanwhile, innovative efforts are being made on the federal level to advance COVID-19 testing. The NIH just launched the Rapid Acceleration of Diagnostics (RADx) Initiative to support a variety of research activities aimed at improving detection of the virus. As I recently highlighted on this blog, one key component of RADx is a “shark tank”-like competition to encourage science and engineering’s most inventive minds to develop rapid, easy-to-use technologies to test for the presence of SARS-CoV-2.

On the serology testing side, the NIH’s National Cancer Institute has been checking out kits that are designed to detect antibodies to SARS-CoV-2 and have found mixed results. In response, the Food and Drug Administration just issued its updated policy on antibody tests for COVID-19. This guidance sets forth precise standards for laboratories and commercial manufacturers that will help to speed the availability of high-quality antibody tests, which in turn will expand the capacity for rapid and widespread testing in the United States.

Finally, it’s important to keep in mind that there are two different types of SARS-CoV-2 tests. Those that test for the presence of viral nucleic acid or protein are used to identify people who are acutely infected and should be immediately quarantined. Tests for IgM and/or IgG antibodies to the virus, if well-validated, indicate a person has previously been infected with COVID-19 and is now potentially immune. Two very different types of tests—two very different meanings.

There’s still a way to go with both virus and antibody testing for COVID-19. But as this study and others begin to piece together the complex puzzle of antibody-mediated immunity, it will be possible to learn more about the human body’s response to SARS-CoV-2 and home in on our goal of achieving safe, effective, and sustained protection against this devastating disease.

Reference:

[1] Antibody responses to SARS-CoV-2 in patients with COVID-19. Long QX, Huang AI, et al. Nat Med. 2020 Apr 29. [Epub ahead of print]

Links:

Coronaviruses (NIH)

NIH Begins Study to Quantify Undetected Cases of Coronavirus Infection,” NIH News Release, April 10, 2020.

NIH mobilizes national innovation initiative for COVID-19 diagnostics,” NIH News Release, April 29, 2020.

Policy for Coronavirus Disease-2019 Tests During the Public Health Emergency (Revised), May 2020 (Food and Drug Administration)


The Challenge of Tracking COVID-19’s Stealthy Spread

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Floating SARS-CoV-2 particles
Credit: CDC/ Alissa Eckert, MS; Dan Higgins, MAMS

As our nation looks with hope toward controlling the coronavirus 2019 disease (COVID-19) pandemic, researchers are forging ahead with efforts to develop and implement strategies to prevent future outbreaks. It sounds straightforward. However, several new studies indicate that containing SARS-CoV-2—the novel coronavirus that causes COVID-19—will involve many complex challenges, not the least of which is figuring out ways to use testing technologies to our best advantage in the battle against this stealthy foe.

The first thing that testing may help us do is to identify those SARS-CoV-2-infected individuals who have no symptoms, but who are still capable of transmitting the virus. These individuals, along with their close contacts, will need to be quarantined rapidly to protect others. These kinds of tests detect viral material and generally analyze cells collected via nasal or throat swabs.

The second way we can use testing is to identify individuals who’ve already been infected with SARS-CoV-2, but who didn’t get seriously ill and can no longer transmit the virus to others. These individuals may now be protected against future infections, and, consequently, may be in a good position to care for people with COVID-19 or who are vulnerable to the infection. Such tests use blood samples to detect antibodies, which are blood proteins that our immune systems produce to attack viruses and other foreign invaders.

A new study, published in Nature Medicine [1], models what testing of asymptomatic individuals with active SARS-CoV-2 infections may mean for future containment efforts. To develop their model, researchers at China’s Guangzhou Medical University and the University of Hong Kong School of Public Health analyzed throat swabs collected from 94 people who were moderately ill and hospitalized with COVID-19. Frequent in-hospital swabbing provided an objective, chronological record—in some cases, for more than a month after a diagnosis—of each patient’s viral loads and infectiousness.

The model, which also factored in patients’ subjective recollections of when they felt poorly, indicates:

• On average, patients became infectious 2.3 days before onset of symptoms.
• Their highest level of potential viral spreading likely peaked hours before their symptoms appeared.
• Patients became rapidly less infectious within a week, although the virus likely remains in the body for some time.

The researchers then turned to data from a separate, previously published study [2], which documented the timing of 77 person-to-person transmissions of SARS-CoV-2. Comparing the two data sets, the researchers estimated that 44 percent of SARS-CoV-2 transmissions occur before people get sick.

Based on this two-part model, the researchers warned that traditional containment strategies (testing only of people with symptoms, contact tracing, quarantine) will face a stiff challenge keeping up with COVID-19. Indeed, they estimated that if more than 30 percent of new infections come from people who are asymptomatic, and they aren’t tested and found positive until 2 or 3 days later, public health officials will need to track down more than 90 percent of their close contacts and get them quarantined quickly to contain the virus.

The researchers also suggested alternate strategies for curbing SARS-CoV-2 transmission fueled by people who are initially asymptomatic. One possibility is digital tracing. It involves creating large networks of people who’ve agreed to install a special tracing app on their smart phones. If a phone user tests positive for COVID-19, everyone with the app who happened to have come in close contact with that person would be alerted anonymously and advised to shelter at home.

The NIH has a team that’s exploring various ways to carry out digital tracing while still protecting personal privacy. The private sector also has been exploring technological solutions, with Apple and Google recently announcing a partnership to develop application programming interfaces (APIs) to allow voluntary digital tracing for COVID-19 [3], The rollout of their first API is expected in May.

Of course, all these approaches depend upon widespread access to point-of-care testing that can give rapid results. The NIH is developing an ambitious program to accelerate the development of such testing technologies; stay tuned for more information about this in a forthcoming blog.

The second crucial piece of the containment puzzle is identifying those individuals who’ve already been infected by SARS-CoV-2, many unknowingly, but who are no longer infectious. Early results from an ongoing study on residents in Los Angeles County indicated that approximately 4.1 percent tested positive for antibodies against SARS-CoV-2 [4]. That figure is much higher than expected based on the county’s number of known COVID-19 cases, but jibes with preliminary findings from a different research group that conducted antibody testing on residents of Santa Clara County, CA [5].

Still, it’s important to keep in mind that SARS-CoV-2 antibody tests are just in the development stage. It’s possible some of these results might represent false positives—perhaps caused by antibodies to some other less serious coronavirus that’s been in the human population for a while.

More work needs to be done to sort this out. In fact, the NIH’s National Institute of Allergy and Infectious Diseases (NIAID), which is our lead institute for infectious disease research, recently launched a study to help gauge how many adults in the U. S. with no confirmed history of a SARS-CoV-2 infection have antibodies to the virus. In this investigation, researchers will collect and analyze blood samples from as many as 10,000 volunteers to get a better picture of SARS-CoV-2’s prevalence and potential to spread within our country.

There’s still an enormous amount to learn about this major public health threat. In fact, NIAID just released its strategic plan for COVID-19 to outline its research priorities. The plan provides more information about the challenges of tracking SARS-CoV-2, as well as about efforts to accelerate research into possible treatments and vaccines. Take a look!

References:

[1] Temporal dynamics in viral shedding and transmissibility of COVID-19. He X, Lau EHY, Wu P, Deng X, Wang J, Hao X, Lau YC, Wong JY, Guan Y, Tan X, Mo X, Chen Y, Liao B, Chen W, Hu F, Zhang Q, Zhong M, Wu Y, Zhao L, Zhang F, Cowling BJ, Li F, Leung GM. Nat Med. 2020 Apr 15. [Epub ahead of publication]

[2] Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. Li, Q. et al. N. Engl. J. Med. 2020 Mar 26;382, 1199–1207.

[3] Apple and Google partner on COVID-19 contact tracing technology. Apple news release, April 10, 2020.

[4] USC-LA County Study: Early Results of Antibody Testing Suggest Number of COVID-19 Infections Far Exceeds Number of Confirmed Cases in Los Angeles County. County of Los Angeles Public Health News Release, April 20, 2020.

[5] COVID-19 Antibody Seroprevalence in Santa Clara County, California. Bendavid E, Mulaney B, Sood N, Sjah S, Ling E, Bromley-Dulfano R, Lai C, Saavedra-Walker R, Tedrow J, Tversky D, Bogan A, Kupiec T, Eichner D, Gupta R, Ioannidis JP, Bhattacharya J. medRxiv, Preprint posted on April 14, 2020.

Links:

Coronavirus (COVID-19) (NIH)

COVID-19, MERS & SARS (NIAID)

NIAID Strategic Plan for COVID-19 Research, FY 2020-2024

NIH Support: National Institute of Allergy and Infectious Diseases


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