COVID-19 Infected Many More Americans in 2020 than Official Tallies Show
Posted on by Dr. Francis Collins
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 . 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.
 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.
COVID-19 Research (NIH)
Sen Pei (Columbia University, New York)
Jeffrey Shaman (Columbia University, New York)
Genome Data Help Track Community Spread of COVID-19
Posted on by Dr. Francis Collins
Contact tracing, a term that’s been in the news lately, is a crucial tool for controlling the spread of SARS-CoV-2, the novel coronavirus that causes COVID-19. It depends on quick, efficient identification of an infected individual, followed by identification of all who’ve recently been in close contact with that person so the contacts can self-quarantine to break the chain of transmission.
Properly carried out, contact tracing can be extremely effective. It can also be extremely challenging when battling a stealth virus like SARS-CoV-2, especially when the virus is spreading rapidly.
But there are some innovative ways to enhance contact tracing. In a new study, published in the journal Nature Medicine, researchers in Australia demonstrate one of them: assembling genomic data about the virus to assist contact tracing efforts. This so-called genomic surveillance builds on the idea that when the virus is passed from person to person over a few months, it can acquire random variations in the sequence of its genetic material. These unique variations serve as distinctive genomic “fingerprints.”
When COVID-19 starts circulating in a community, researchers can fingerprint the genomes of SARS-CoV-2 obtained from newly infected people. This timely information helps to tell whether that particular virus has been spreading locally for a while or has just arrived from another part of the world. It can also show where the viral subtype has been spreading through a community or, best of all, when it has stopped circulating.
The recent study was led by Vitali Sintchenko at the University of Sydney. His team worked in parallel with contact tracers at the Ministry of Health in New South Wales (NSW), Australia’s most populous state, to contain the initial SARS-CoV-2 outbreak from late January through March 2020.
The team performed genomic surveillance, using sequencing data obtained within about five days, to understand local transmission patterns. They also wanted to compare what they learned from genomic surveillance to predictions made by a sophisticated computer model of how the virus might spread amongst Australia’s approximately 24 million citizens.
Of the 1,617 known cases in Sydney over the three-month study period, researchers sequenced viral genomes from 209 (13 percent) of them. By comparing those sequences to others circulating overseas, they found a lot of sequence diversity, indicating that the novel coronavirus had been introduced to Sydney many times from many places all over the world.
They then used the sequencing data to better understand how the virus was spreading through the local community. Their analysis found that the 209 cases under study included 27 distinct genomic fingerprints. Based on the close similarity of their genomic fingerprints, a significant share of the COVID-19 cases appeared to have stemmed from the direct spread of the virus among people in specific places or facilities.
What was most striking was that the genomic evidence helped to provide information that contact tracers otherwise would have lacked. For instance, the genomic data allowed the researchers to identify previously unsuspected links between certain cases of COVID-19. It also helped to confirm other links that were otherwise unclear.
All told, researchers used the genomic evidence to cluster almost 40 percent of COVID-19 cases (81 of 209) for which the community-based data alone couldn’t identify a known contact source for the infection. That included 26 cases in which an individual who’d recently arrived in Australia from overseas spread the infection to others who hadn’t traveled. The genomic information also helped to identify likely sources in the community for another 15 locally acquired cases that weren’t known based on community data.
The researchers compared their genome surveillance data to SARS-CoV-2’s expected spread as modeled in a computer simulation based on travel to and from Australia over the time period in question. Because the study involved just 13 percent of all known COVID-19 cases in Sydney between late January through March, it’s not surprising that the genomic data presents an incomplete picture, detecting only a portion of the possible chains of transmission expected in the simulation model.
Nevertheless, the findings demonstrate the value of genomic data for tracking the virus and pinpointing exactly where in the community it is spreading. This can help to fill in important gaps in the community-based data that contact tracers often use. Even more exciting, by combining traditional contact tracing, genomic surveillance, and mathematical modeling with other emerging tools at our disposal, it may be possible to get a clearer picture of the movement of SARS-CoV-2 and put more targeted public health measures in place to slow and eventually stop its deadly spread.
 Revealing COVID-19 transmission in Australia by SARS-CoV-2 genome sequencing and agent-based modeling. Rockett RJ, Arnott A, Lam C, et al. Nat Med. 2020 July 9. [Published online ahead of print]
Coronavirus (COVID-19) (NIH)
Vitali Sintchenko (University of Sydney, Australia)
Can Smart Phone Apps Help Beat Pandemics?
Posted on by Dr. Francis Collins
In recent weeks, most of us have spent a lot of time learning about coronavirus disease 2019 (COVID-19) and thinking about what’s needed to defeat this and future pandemic threats. When the time comes for people to come out of their home seclusion, how will we avoid a second wave of infections? One thing that’s crucial is developing better ways to trace the recent contacts of individuals who’ve tested positive for the disease-causing agent—in this case, a highly infectious novel coronavirus.
Traditional contact tracing involves a team of public health workers who talk to people via the phone or in face-to-face meetings. This time-consuming, methodical process is usually measured in days, and can even stretch to weeks in complex situations with multiple contacts. But researchers are now proposing to take advantage of digital technology to try to get contact tracing done much faster, perhaps in just a few hours.
Most smart phones are equipped with wireless Bluetooth technology that creates a log of all opt-in mobile apps operating nearby—including opt-in apps on the phones of nearby people. This has prompted a number of research teams to explore the idea of creating an app to notify individuals of exposure risk. Specifically, if a smart phone user tests positive today for COVID-19, everyone on their recent Bluetooth log would be alerted anonymously and advised to shelter at home. In fact, in a recent paper in the journal Science, a British research group has gone so far to suggest that such digital tracing may be valuable in the months ahead to improve our chances of keeping COVID-19 under control .
The British team, led by Luca Ferretti, Christophe Fraser, and David Bonsall, Oxford University, started their analyses using previously published data on COVID-19 outbreaks in China, Singapore, and aboard the Diamond Princess cruise ship. With a focus on prevention, the researchers compared the different routes of transmission, including from people with and without symptoms of the infection.
Based on that data, they concluded that traditional contact tracing was too slow to keep pace with the rapidly spreading COVID-19 outbreaks. During the three outbreaks studied, people infected with the novel coronavirus had a median incubation period of about five days before they showed any symptoms of COVID-19. Researchers estimated that anywhere from one-third to one-half of all transmissions came from asymptomatic people during this incubation period. Moreover, assuming that symptoms ultimately arose and an infected person was then tested and received a COVID-19 diagnosis, public health workers would need at least several more days to perform the contact tracing by traditional means. By then, they would have little chance of getting ahead of the outbreak by isolating the infected person’s contacts to slow its rate of transmission.
When they examined the situation in China, the researchers found that available data show a correlation between the roll-out of smart phone contact-tracing apps and the emergence of what appears to be sustained suppression of COVID-19 infection. Their analyses showed that the same held true in South Korea, where data collected through a smart phone app was used to recommend quarantine.
Despite its potential benefits in controlling or even averting pandemics, the British researchers acknowledged that digital tracing poses some major ethical, legal, and social issues. In China, people were required to install the digital tracing app on their phones if they wanted to venture outside their immediate neighborhoods. The app also displayed a color-coded warning system to enforce or relax restrictions on a person’s movements around a city or province. The Chinese app also relayed to a central database the information that it had gathered on phone users’ movements and COVID-19 status, raising serious concerns about data security and privacy of personal information.
In their new paper, the Oxford team, which included a bioethicist, makes the case for increased social dialogue about how best to employ digital tracing in ways the benefit human health. This is a far-reaching discussion with implications far beyond times of pandemic. Although the team analyzed digital tracing data for COVID-19, the algorithms that drive these apps could be adapted to track the spread of other common infectious diseases, such as seasonal influenza.
The study’s authors also raised another vital point. Even the most-sophisticated digital tracing app won’t be of much help if smart phone users don’t download it. Without widespread installation, the apps are unable to gather enough data to enable effective digital tracing. Indeed, the researchers estimate that about 60 percent of new COVID-19 cases in a community would need to be detected–and roughly the same percentage of contacts traced—to squelch the spread of the deadly virus.
Such numbers have app designers working hard to discover the right balance between protecting public health and ensuring personal rights. That includes NIH grantee Trevor Bedford, Fred Hutchinson Cancer Research Center, Seattle. He and his colleagues just launched NextTrace, a project that aims to build an opt-in app community for “digital participatory contact tracing” of COVID-19. Here at NIH, we have a team that is actively exploring the kind of technology that could achieve the benefits without unduly compromising personal privacy.
Bedford emphasizes that he and his colleagues aren’t trying to duplicate efforts already underway. Rather, they want to collaborate with others help to build a scientifically and ethically sound foundation for digital tracing aimed at improving the health of all humankind.
 Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Ferretti L, Wymant C, Kendall M, Zhao L, Nurtay A, Abeler-Dörner L, Parker M, Bonsall D, Fraser C. Science. 2020 Mar 31. [Epub ahead of print]
Coronavirus (COVID-19) (NIH)
COVID-19, MERS & SARS (National Institute of Allergy and Infectious Diseases/NIH)
NextTrace (Fred Hutchinson Cancer Research Center, Seattle)
Bedford Lab (Fred Hutchinson Cancer Research Center)
NIH Support: National Institute of General Medical Sciences