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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.


[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.


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

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.


[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.


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