Skip to main content

COVID-19 infections

COVID-19 Vaccines Protect the Family, Too

Posted on by

Multigenerational family walks at the beach
Credit: Shutterstock

Any of the available COVID-19 vaccines offer remarkable personal protection against the coronavirus SARS-CoV-2. So, it also stands to reason that folks who are vaccinated will reduce the risk of spreading the virus to family members within their households. That protection is particularly important when not all family members can be immunized—as when there are children under age 12 or adults with immunosuppression in the home. But just how much can vaccines help to protect families from COVID-19 when only some, not all, in the household have immunity?

A Swedish study, published recently in the journal JAMA Internal Medicine, offers some of the first hard figures on this topic, and the findings are quite encouraging [1]. The data show that people without any immunity against COVID-19 were at considerably lower risk of infection and hospitalization when other members of their family had immunity, either from a natural infection or vaccination. In fact, the protective effect on family members went up as the number of immune family members increased.

The findings come from a team led by Peter Nordström, Umeå University, Sweden. Like in the United States, vaccinations in Sweden initially were prioritized for high-risk groups and people with certain preexisting conditions. As a result, Swedish families have functioned, often in close contact, as a mix of immune and susceptible individuals over the course of the pandemic.

To explore these family dynamics in greater detail, the researchers relied on nationwide registries to identify all Swedes who had immunity to SARS-COV-2 from either a confirmed infection or vaccination by May 26, 2021. The researchers identified more than 5 million individuals who’d been either diagnosed with COVID-19 or vaccinated and then matched them to a control group without immunity. They also limited the analysis to individuals in families with two to five members of mixed immune status.

This left them with about 1.8 million people from more than 800,000 families. The situation in Sweden is also a little unique from most Western nations. Somewhat controversially, the Swedish government didn’t order a mandatory citizen quarantine to slow the spread of the virus.

The researchers found in the data a rising protective effect for those in the household without immunity as the number of immune family members increased. Families with one immune family member had a 45 to 61 percent lower risk of a COVID-19 infection in the home than those who had none. Those with two immune family members enjoyed more protection, with a 75 to 86 percent reduction in risk of COVID-19. For those with three or four immune family members, the protection went up to more than 90 percent, topping out at 97 percent protection. The results were similar when the researchers limited the analysis to COVID-19 illnesses serious enough to warrant a hospital stay.

The findings confirm that vaccination is incredibly important not only for individual protection, but also for reducing transmission, especially within families and those with whom we’re in close physical contact. It’s also important to note that the findings apply to the original SARS-CoV-2 variant, which was dominant when the study was conducted. But we know that the vaccines offer good protection against Delta and other variants of concern.

These results show quite clearly that vaccines offer protection for individuals who lack immunity, with important implications for finally ending this pandemic. This doesn’t change the fact that all those who can and still need to get fully vaccinated should do so as soon as possible. If you are eligible for a booster shot, that’s something to consider, too. But, if for whatever reason you haven’t gotten vaccinated just yet, perhaps these new findings will encourage you to do it now for the sake of those other people you care about. This is a chance to love your family—and love your neighbor.

Reference:

[1] Association between risk of COVID-19 infection in nonimmune individuals and COVID-19 immunity in their family members. Nordström P, Ballin M, Nordström A. JAMA Intern Med. 2021 Oct 11.

Links:

COVID-19 Research (NIH)

Peter Nordström (Umeå University, Sweden)


COVID-19 Infected Many More Americans in 2020 than Official Tallies Show

Posted on by

Map of U.S.. Counties showing varying levels of COVID-19 infection
Caption: Percentage of people in communities across the United States infected by the novel coronavirus that causes COVID-19 as of December 2020. Credit: Pei S, Nature, 2021.

At the end of last year, you may recall hearing news reports that the number of COVID-19 cases in the United States had topped 20 million. While that number came as truly sobering news, it also likely was an underestimate. Many cases went undetected due to limited testing early in the year and a large number of infections that produced mild or no symptoms.

Now, a recent article published in Nature offers a more-comprehensive estimate that puts the true number of infections by the end of 2020 at more than 100 million [1]. That’s equal to just under a third of the U.S. population of 328 million. This revised number shows just how rapidly this novel coronavirus spread through the country last year. It also brings home just how timely the vaccines have been—and continue to be in 2021—to protect our nation’s health in this time of pandemic.

The work comes from NIH grantee Jeffrey Shaman, Sen Pei, and colleagues, Columbia University, New York. As shown above in the map, the researchers estimated the percentage of people who had been infected with SARS-CoV-2, the novel coronavirus that causes COVID-19, in communities across the country through December 2020.

To generate this map, they started with existing national data on the number of coronavirus cases (both detected and undetected) in 3,142 U.S. counties and major metropolitan areas. They then factored in data from the Centers for Disease Control and Prevention (CDC) on the number of people who tested positive for antibodies against SARS-CoV-2. These CDC data are useful for picking up on past infections, including those that went undetected.

From these data, the researchers calculated that only about 11 percent of all COVID-19 cases were confirmed by a positive test result in March 2020. By the end of the year, with testing improvements and heightened public awareness of COVID-19, the ascertainment rate (the number of infections that were known versus unknown) rose to about 25 percent on average. This measure also varied a lot across the country. For instance, the ascertainment rates in Miami and Phoenix were higher than the national average, while rates in New York City, Los Angeles, and Chicago were lower than average.

How many people were potentially walking around with a contagious SARS-CoV-2 infection? The model helps to answer this, too. On December 31, 2020, the researchers estimate that 0.77 percent of the U.S. population had a contagious infection. That’s about 1 in every 130 people on average. In some places, it was much higher. In Los Angeles, for example, nearly 1 in 40 (or 2.42 percent) had a SARS-CoV-2 infection as they rang in the New Year.

Over the course of the year, the fatality rate associated with COVID-19 dropped, at least in part due to earlier diagnosis and advances in treatment. The fatality rate went from 0.77 percent in April to 0.31 percent in December. While this is great news, it still shows that COVID-19 remains much more dangerous than seasonal influenza (which has a fatality rate of 0.08 percent).

Today, the landscape has changed considerably. Vaccines are now widely available, giving many more people immune protection without ever having to get infected. And yet, the rise of the Delta and other variants means that breakthrough infections and reinfections—which the researchers didn’t account for in their model—have become a much bigger concern.

Looking ahead to the end of 2021, Americans must continue to do everything they can to protect their communities from the spread of this terrible virus. That means getting vaccinated if you haven’t already, staying home and getting tested if you’ve got symptoms or know of an exposure, and taking other measures to keep yourself and your loved ones safe and well. These measures we take now will influence the infection rates and susceptibility to SARS-CoV-2 in our communities going forward. That will determine what the map of SARS-CoV-2 infections will look like in 2021 and beyond and, ultimately, how soon we can finally put this pandemic behind us.

Reference:

[1] Burden and characteristics of COVID-19 in the United States during 2020. Pei S, Yamana TK, Kandula S, Galanti M, Shaman J. Nature. 2021 Aug 26.

Links:

COVID-19 Research (NIH)

Sen Pei (Columbia University, New York)

Jeffrey Shaman (Columbia University, New York)


New Metric Identifies Coronavirus Hotspots in Real Time

Posted on by

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


How Immunity Generated from COVID-19 Vaccines Differs from an Infection

Posted on by

Orginal viral spike is shown binding to antibody from vaccine and from infection. Variant spikes only bind to antibody from vaccine.

A key issue as we move closer to ending the pandemic is determining more precisely how long people exposed to SARS-CoV-2, the COVID-19 virus, will make neutralizing antibodies against this dangerous coronavirus. Finding the answer is also potentially complicated with new SARS-CoV-2 “variants of concern” appearing around the world that could find ways to evade acquired immunity, increasing the chances of new outbreaks.

Now, a new NIH-supported study shows that the answer to this question will vary based on how an individual’s antibodies against SARS-CoV-2 were generated: over the course of a naturally acquired infection or from a COVID-19 vaccine. The new evidence shows that protective antibodies generated in response to an mRNA vaccine will target a broader range of SARS-CoV-2 variants carrying “single letter” changes in a key portion of their spike protein compared to antibodies acquired from an infection.

These results add to evidence that people with acquired immunity may have differing levels of protection to emerging SARS-CoV-2 variants. More importantly, the data provide further documentation that those who’ve had and recovered from a COVID-19 infection still stand to benefit from getting vaccinated.

These latest findings come from Jesse Bloom, Allison Greaney, and their team at Fred Hutchinson Cancer Research Center, Seattle. In an earlier study, this same team focused on the receptor binding domain (RBD), a key region of the spike protein that studs SARS-CoV-2’s outer surface. This RBD is especially important because the virus uses this part of its spike protein to anchor to another protein called ACE2 on human cells before infecting them. That makes RBD a prime target for both naturally acquired antibodies and those generated by vaccines. Using a method called deep mutational scanning, the Seattle group’s previous study mapped out all possible mutations in the RBD that would change the ability of the virus to bind ACE2 and/or for RBD-directed antibodies to strike their targets.

In their new study, published in the journal Science Translational Medicine, Bloom, Greaney, and colleagues looked again to the thousands of possible RBD variants to understand how antibodies might be expected to hit their targets there [1]. This time, they wanted to explore any differences between RBD-directed antibodies based on how they were acquired.

Again, they turned to deep mutational scanning. First, they created libraries of all 3,800 possible RBD single amino acid mutants and exposed the libraries to samples taken from vaccinated individuals and unvaccinated individuals who’d been previously infected. All vaccinated individuals had received two doses of the Moderna mRNA vaccine. This vaccine works by prompting a person’s cells to produce the spike protein, thereby launching an immune response and the production of antibodies.

By closely examining the results, the researchers uncovered important differences between acquired immunity in people who’d been vaccinated and unvaccinated people who’d been previously infected with SARS-CoV-2. Specifically, antibodies elicited by the mRNA vaccine were more focused to the RBD compared to antibodies elicited by an infection, which more often targeted other portions of the spike protein. Importantly, the vaccine-elicited antibodies targeted a broader range of places on the RBD than those elicited by natural infection.

These findings suggest that natural immunity and vaccine-generated immunity to SARS-CoV-2 will differ in how they recognize new viral variants. What’s more, antibodies acquired with the help of a vaccine may be more likely to target new SARS-CoV-2 variants potently, even when the variants carry new mutations in the RBD.

It’s not entirely clear why these differences in vaccine- and infection-elicited antibody responses exist. In both cases, RBD-directed antibodies are acquired from the immune system’s recognition and response to viral spike proteins. The Seattle team suggests these differences may arise because the vaccine presents the viral protein in slightly different conformations.

Also, it’s possible that mRNA delivery may change the way antigens are presented to the immune system, leading to differences in the antibodies that get produced. A third difference is that natural infection only exposes the body to the virus in the respiratory tract (unless the illness is very severe), while the vaccine is delivered to muscle, where the immune system may have an even better chance of seeing it and responding vigorously.

Whatever the underlying reasons turn out to be, it’s important to consider that humans are routinely infected and re-infected with other common coronaviruses, which are responsible for the common cold. It’s not at all unusual to catch a cold from seasonal coronaviruses year after year. That’s at least in part because those viruses tend to evolve to escape acquired immunity, much as SARS-CoV-2 is now in the process of doing.

The good news so far is that, unlike the situation for the common cold, we have now developed multiple COVID-19 vaccines. The evidence continues to suggest that acquired immunity from vaccines still offers substantial protection against the new variants now circulating around the globe.

The hope is that acquired immunity from the vaccines will indeed produce long-lasting protection against SARS-CoV-2 and bring an end to the pandemic. These new findings point encouragingly in that direction. They also serve as an important reminder to roll up your sleeve for the vaccine if you haven’t already done so, whether or not you’ve had COVID-19. Our best hope of winning this contest with the virus is to get as many people immunized now as possible. That will save lives, and reduce the likelihood of even more variants appearing that might evade protection from the current vaccines.

Reference:

[1] Antibodies elicited by mRNA-1273 vaccination bind more broadly to the receptor binding domain than do those from SARS-CoV-2 infection. Greaney AJ, Loes AN, Gentles LE, Crawford KHD, Starr TN, Malone KD, Chu HY, Bloom JD. Sci Transl Med. 2021 Jun 8.

Links:

COVID-19 Research (NIH)

Bloom Lab (Fred Hutchinson Cancer Research Center, Seattle)

NIH Support: National Institute of Allergy and Infectious Diseases


Tracking the Evolution of a ‘Variant of Concern’ in Brazil

Posted on by

P.1 Variant of SARS-CoV-2 in the center of standard SARS-CoV-2. Arrows move out from the variant

By last October, about three out of every four residents of Manaus, Brazil already had been infected with SARS-CoV-2, the virus that causes COVID-19 [1]. And yet, despite hopes of achieving “herd immunity” in this city of 2.2 million in the Amazon region, the virus came roaring back in late 2020 and early 2021 to cause a second wave of illness and death [2]. How is this possible?

The answer offers a lesson in viral evolution, especially when an infectious virus such as SARS-CoV-2 replicates and spreads through a population largely unchecked. In a recent study in the journal Science, researchers tied the city’s resurgence of SARS-CoV-2 to the emergence and rapid spread of a new SARS-CoV-2 “variant of concern” known as P.1 [3]. This variant carries a unique constellation of mutations that allow it not only to sneak past the human immune system and re-infect people, but also to be about twice as transmissible as earlier variants.

To understand how this is possible, consider that each time the coronavirus SARS-CoV-2 makes copies of itself in an infected person, there’s a chance a mistake will be made. Each mistake can produce a new variant that may go on to make more copies of itself. In most cases, those random errors are of little to no consequence. This is evolution in action.

But sometimes a spelling change can occur that benefits the virus. In the special case of patients with suppressed immune systems, the virus can have ample opportunity to accrue an unusually high number of mutations. Variants carrying beneficial mutations can make more copies of themselves than other variants, allowing them to build their numbers and spread to cause more infection.

At this advanced stage of the COVID-19 pandemic, such rapidly spreading new variants remain cause for serious concern. That includes variants such as B.1.351, which originated in South Africa; B.1.1.7 which emerged in the United Kingdom; and now P.1 from Manaus, Brazil.

In the new study, Nuno Faria and Samir Bhatt, Imperial College London, U.K., and Ester Cerdeira Sabino, Universidade de Sao Paulo, Brazil, and their colleagues sequenced SARS-CoV-2 genomes from 184 patient samples collected in Manaus in November and December 2020. The research was conducted under the auspices of the Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology (CADDE), a project focused on viral genomics and epidemiology for public health.

Those genomic data revealed the P.1 variant had acquired 17 new mutations. Ten were in the spike protein, which is the segment of the virus that binds onto human cells and the target of current COVID-19 vaccines. In fact, the new work reveals that three of these spike protein mutations make it easier for the P.1 spike to bind the human ACE2 receptor, which is SARS-CoV-2’s preferred entry point.

The first P.1 variant case was detected by genomic surveillance on December 6, 2020, after which it spread rapidly. Through further evolutionary analysis, the team estimates that P.1 must have emerged, undetected for a brief time, in mid-November 2020.

To understand better how the P.1 variant led to such an explosion of new COVID-19 cases, the researchers developed a mathematical model that integrated the genomic data with mortality data. The model suggests that P.1 may be 1.7 to 2.4 times more transmissible than earlier variants. They also estimate that a person previously infected with a variant other than P.1 will have only 54 percent to 79 percent protection against a subsequent infection with P.1.

The researchers also observed an increase in mortality following the emergence of the P.1 variant. However, it’s not yet clear if that’s an indication P.1 is inherently more deadly than earlier variants. It’s possible the increased mortality is related primarily to the extra stress on the healthcare system in Manaus from treating so many people with COVID-19.

These findings are yet another reminder of the importance of genomic surveillance and international data sharing for detecting and characterizing emerging SARS-CoV-2 variants quickly. It’s worth noting that at about the same time this variant was detected in Brazil, it also was reported in four individuals who had traveled to Brazil from Japan. The P.1 variant continues to spread rapidly across Brazil. It has also been detected in more than 37 countries [4], including the United States, where it now accounts for more than 1 percent of new cases [5].

No doubt you are wondering what this means for vaccines, such as the Pfizer and Moderna mRNA vaccines, that have been used to immunize (at least one dose) over 140 million people in the United States. Here the news is encouraging. Serum from individuals who received the Pfizer vaccine had titers of neutralizing antibodies that were only slightly reduced for P.1 compared to the original SARS-CoV-2 virus [6]. Therefore, the vaccine is predicted to be highly protective. This is another example of a vaccine providing more protection than a natural infection.

The United States has made truly remarkable progress in combating COVID-19, but we must heed this lesson from Manaus: this terrible pandemic isn’t over just yet. While the P.1 variant remains at low levels here for now, the “U.K. variant” B.1.1.7 continues to spread rapidly and now is the most prevalent variant circulating in the U.S., accounting for 44 percent of new cases [6]. Fortunately, the mRNA vaccines also work well against B.1.1.7.

We must continue to do absolutely everything possible, individually and collectively, to prevent these new SARS-CoV-2 variants from slowing or even canceling the progress made over the last year. We need to remain vigilant for just a while longer, while encouraging our friends, neighbors, and loved ones to get vaccinated.

References:

[1] Three-quarters attack rate of SARS-CoV-2 in the Brazilian Amazon during a largely unmitigated epidemic. Buss, L. F., C. A. Prete, Jr., C. M. M. Abrahim, A. C. Dye, V. H. Nascimento, N. R. Faria and E. C. Sabino et al. (2021). Science 371(6526): 288-292.

[2] Resurgence of COVID-19 in Manaus, Brazil, despite high seroprevalence. Sabino EC, Buss LF, Carvalho MPS, Prete Jr CCA, Crispim MAE, Fraiji NA, Pereira RHM, Paraga KV, Peixoto PS, Kraemer MUG, Oikawa MJ, Salomon T, Cucunuba ZM, Castro MC, Santos AAAS, Nascimento VH, Pereira HS, Ferguson NM, Pybus OG, Kucharski A, Busch MP, Dye C, Faria NR Lancet. 2021 Feb 6;397(10273):452-455.

[3] Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil. Faria NR, Mellan TA, Whittaker C, Claro IM, Fraiji NA, Carvalho MDPSS, Pybus OG, Flaxman S, Bhatt S, Sabino EC et al. Science. 2021 Apr 14:eabh2644.

[4] GRINCH Global Report Investigating novel coronavirus haplotypes. PANGO Lineages.

[5] COVID Data Tracker. Variant Proportions. Centers for Disease Control and Prevention.

[6] Antibody evasion by the P.1 strain of SARS-CoV-2. Dejnirattisai W, Zhou D, Supasa P, Liu C, Mongkolsapaya J, Ren J, Stuart DI, Screaton GR, et al. Cell. 2021 Mar 30:S0092-8674(21)00428-1.

Links:

COVID-19 Research (NIH)

Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology (CADDE)

Nuno Faria (Imperial College, London, U.K.)

Samir Bhatt (Imperial College)

Ester Cerdeira Sabino (Universidade de Sao Paulo, Brazil)

NIH Support: National Institute of Allergy and Infectious Diseases


Next Page