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Learning to Protect Communities with COVID-19 Home Testing Programs

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Credit: Say Yes! COVID Test

With most kids now back in school, parents face a new everyday concern: determining whether their child’s latest cough or sneeze might be a sign of COVID-19. If so, parents will want to keep their child at home to protect other students and staff, while also preventing the spread of the virus in their communities. And if it’s the parent who has a new cough, they also will want to know if the reason is COVID-19 before going to work or the store.

Home tests are now coming online to help concerned people make the right choice quickly. As more COVID-19 home tests enter the U.S. marketplace, research continues to help optimize their use. That’s why NIH and the Centers for Disease Control and Prevention (CDC) are teaming up in several parts of the country to provide residents age 2 and older with free home-testing kits for COVID-19. These reliable, nasal swab tests provide yes-or-no answers in about 15 minutes for parents and anyone else concerned about their possible exposure to the novel coronavirus.

The tests are part of an initiative called Say Yes! COVID Test (SYCT) that’s evaluating how best to implement home-testing programs within range of American communities, both urban and rural. The lessons learned are providing needed science-based data to help guide public health officials who are interested in implementing similar home-testing programs in communities throughout their states.

After successful eight-week pilot programs this past spring and summer in parts of North Carolina, Tennessee, and Michigan, SYCT is partnering this fall with four new communities. They are Fulton County, GA; Honolulu County, HI; and Louisville Metro, KY; with another community in the Midwest to be announced later this month.

The Georgia and Hawaii partnerships, launched on September 20, are already off to a flying start. In Fulton County, home to Atlanta and several small cities, 21,673 direct-to-consumer orders (173,384 tests) have already been received. In Honolulu County, demand for the tests has exceeded all expectations, with 91,000 orders received in the first week (728,000 tests). The online ordering has now closed in Hawaii, and the remaining tests will be distributed on the ground through the local public health department.

SYCT offers the Quidel QuickVue® At-Home COVID-19 test, which is supplied through the NIH Rapid Acceleration of Diagnostics (RADx) initiative. The antigen test uses a self-collected nasal swab sample that is placed in a test tube containing solution, followed by a test strip. Colored lines that appear on the test strip indicate a positive or negative result—similar to a pregnancy test.

The program allows residents in participating counties to order free home tests online or for in-person pick up at designated sites in their community. Each resident can ask for eight rapid tests, which equals two weekly tests over four weeks. An easy-to-navigate website like this one and a digital app, developed by initiative partner CareEvolution, are available for residents to order their tests, sign-up for testing reminders, and allow voluntary test result reporting to the public health department.

SYCT will generate data to answer several important questions about self or home-testing. They include questions about consumer demand, ensuring full community access, testing behavior, willingness to report test results, and, above all, effectiveness in controlling the spread of SARS-CoV-2, the coronavirus that causes COVID-19

Researchers at the University of North Carolina-Chapel Hill; Duke University, Durham, NC; and the UMass Chan Medical School, Worcester, MA, will help crunch the data and look for guiding themes. They will also conduct a study pre- and post-intervention to evaluate levels of SARS-CoV-2 in the community, including using measures of virus in wastewater. In addition, researchers will compare their results to other counties similar in size and infection rates, but that are not participating in a free testing initiative.

The NIH and CDC are exploring ways to scale a SYCT-like program nationally to communities experiencing surges in COVID-19. The Biden Administration also recently invoked the Defense Production Act to purchase millions of COVID-19 home tests to help accelerate their availability and offer them at a lower cost to more Americans. That encompasses many different types of people, including concerned parents who need a quick-and-accurate answer on whether their children’s cough or sneeze is COVID-19.

Links:

COVID-19 Research (NIH)

Say Yes! COVID Test

Rapid Acceleration of Diagnostics (RADx) (NIH)

NIH Support: National Institute of Biomedical Imaging and Bioengineering; National Heart, Lung, and Blood Institute; National Institute on Minority Health and Health Disparities


New Metric Identifies Coronavirus Hotspots in Real Time

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High viral load found from PCR helps to predict hotspots

During the pandemic, it’s been critical to track in real time where the coronavirus is spreading at home and abroad. But it’s often hard for public health officials to know whether changes in the reported number of COVID-19 cases over time truly reflect the spread of the virus or whether they are confounded by changes in testing levels or lags in the reporting of results.

Now, NIH-funded researchers have discovered a clever workaround to detect more accurately where COVID-19 hotspots are emerging. As published in the journal Science, the new approach focuses on the actual amount of virus present in a positive COVID diagnostic test [1], not just whether the test is positive or negative. What’s even better is these data on a person’s “viral load” are readily available from polymerase chain reaction, or PCR, tests that are the “gold standard” for detecting SARS-CoV-2, the virus responsible for COVID-19. In fact, if you’ve been tested for COVID-19, there’s a good chance you’ve had a PCR-based test.

Here’s how a PCR test for COVID-19 works. After a person provides a nasal swab or saliva sample, any genetic material in the sample is extracted and prepared for the PCR machine. It uses special nucleic acid primers that, if any genetic material from SARS-CoV-2 is present, will make millions more copies of them and result in a positive test result. PCR is an enzymatic reaction that works by running many cycles of heating and cooling; each cycle results in doubling of the genetic material present in the original sample.

But it turns out that PCR can go beyond a simple “yes” or “no” test result. It’s also possible to get some sense of how much coronavirus is present in a positive sample based on the number of cycles required to make enough copies of its genetic material to get the “yes” result. This measure is known as the “cycle threshold,” or Ct, value.

When a sample is run with lots of virus in it, the PCR machine doesn’t need to make so many cycles to reach detectable levels—and the Ct value is considered low. But, when the virus is barely present in a sample, the machine needs to run more cycles before it will reach the threshold for detection. In this case, the Ct value is high. This makes the Ct metric a bit counterintuitive: low Ct means a high level of infection, and high Ct means a low level of infection.

In the new study, researchers in Michael Mina’s lab, Harvard T. H. Chan School of Public Health, Boston, including James Hay and Lee Kennedy-Shaffer, wanted to use Ct values to understand better the overall trajectory of the spread of SARS-CoV-2. Their idea was a little out of the box, since Ct values weren’t being factored into a diagnostic testing process that was set up to give people a yes-or-no answer about COVID-19 status. In fact, Ct values were often discarded.

The team members had a hunch that the amount of virus in patient samples would vary based on whether an outbreak is increasing or declining. Their reasoning was that during an outbreak, when SARS-CoV-2 is spreading rapidly through a community, a larger proportion of infected individuals will have recently contracted the virus than when it is spreading more slowly. The researchers also knew that the virus reaches its peak level in humans soon after infection (generally a couple of days before symptoms begin), and then falls to very low but still detectable levels over the course of weeks or sometimes even months. So, when viral load within samples is highest—and Ct values are lowest—it suggests an outbreak of SARS-CoV-2 is underway. As an outbreak slows and cases fall, viral loads should fall and Ct values rise.

The researchers found that just 30 positive PCR test results on a single day were enough to give an accurate real-time estimate of the growth rate of SARS-CoV-2 infections based on Ct values. With Ct values from multiple time points, it was possible to reconstruct the epidemic curve and estimate the true number of people infected. They found that even Ct values collected from a single location at a single point in time could provide extremely valuable information about the growth or decline of an outbreak.

The findings suggest that these data can now be captured and put to good use as a key metric for decision-making and gauging the success of the pandemic response going forward. It’s also important to note that the value of these data are not unique to COVID-19 and the ongoing pandemic. It appears this can be extremely useful new way to monitor the course of other viral outbreaks, now and in the future, in a way that’s less susceptible to the vagaries of testing. The hope is that this will mean even greater success in capturing viral outbreaks and mobilizing resources in real time to the places where they are most needed.

Reference:

[1] Estimating epidemiologic dynamics from cross-sectional viral load distributions. Hay JA, Kennedy-Shaffer L, Kanjilal S, Lennon NJ, Gabriel SB, Lipsitch M, Mina MJ. Science. 2021 Jun 3.

Links:

COVID-19 Research (NIH)

Michael Mina (Harvard T. H. Chan School of Public Health, Boston)

NIH Support: Common Fund, National Institute of General Medical Sciences; National Cancer Institute


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