epidemiology
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 [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)
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.
Reference:
[1] 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]
Links:
Coronavirus (COVID-19) (NIH)
Vitali Sintchenko (University of Sydney, Australia)
Public Health Policies Have Prevented Hundreds of Millions of Coronavirus Infections
Posted on by Dr. Francis Collins
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.
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 [1].
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.
Reference:
[1] 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]
Links:
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
Uncovering a Hidden Zika Outbreak in Cuba
Posted on by Dr. Francis Collins
When Brazilian health officials discovered four years ago that the mosquito-borne Zika virus could cause severe birth defects and other serious health problems, it prompted a major effort across the Americas to curb the infection by controlling mosquitoes and issuing travel advisories. By mid-2017, the hard work seemed to have paid off, and reports of new Zika infections had nearly stopped.
But it turns out Zika may be tougher to control than once thought. New research shows that a large, previously hidden outbreak of Zika virus disease occurred in Cuba, just when it looked like the worst of the epidemic was over. The finding suggests that the Zika virus can linger over long periods, and that mosquito control efforts alone may slow, but not necessarily stop, the march of this potentially devastating infectious disease.
When combating global epidemics, it’s critical to track the spread of dangerous viruses from one place to the next. But some viruses can be tougher to monitor than others, and that certainly has been the case with Zika in the Americas. Though the virus can harm unborn children, many people infected with Zika never feel lousy enough to go to the doctor. Those who do often have symptoms that overlap with other prevalent tropical diseases, such as dengue and chikungunya fever, making it hard to recognize Zika.
That’s why in Brazil, where Zika arrived in the Americas by early 2014, this unexpected viral intruder went undetected for well over a year. By then, it had spread unnoticed to Honduras, circulating rapidly to other Central American nations and Mexico—likely by late 2014 and into 2015.
In the United States, even with close monitoring, a small local outbreak of Zika virus in Florida also went undetected for about three months in 2016 [1]. Then, in 2017, Florida officials began noticing something strange: new cases of Zika infection in people who had traveled to Cuba.
This came as a real surprise because Cuba, unlike most other Caribbean islands, was thought to have avoided an outbreak. What’s more, by then the Zika epidemic in the Americas had slowed to a trickle, prompting the World Health Organization to delist it as a global public health emergency of international concern.
Given the Cuban observation, some wondered whether the Zika epidemic in the Americas was really over. Among them was an NIH-supported research team, including Nathan Grubaugh, Yale School of Public Health, New Haven, CT; Sharon Isern and Scott Michael, Florida Gulf Coast University, Fort Myers; and Kristian Andersen, The Scripps Research Institute, La Jolla, CA, who worked closely with the Florida Department of Health, including Andrea Morrison.
As published in Cell, the team was able to document a previously unreported outbreak in Cuba after the epidemic had seemingly ended [2]. Interestingly, another research group in Spain also recently made a similar observation about Zika in Cuba [3].
In the Cell paper, the researchers show that between June 2017 and October 2018, all but two of 155 cases—a whopping 98 percent of travel-associated Zika infections—traced back to Cuba. Further analysis suggests that the outbreak in Cuba was likely of similar magnitude to outbreaks that occurred in other Caribbean nations.
Their estimates suggest there were likely many thousands of Zika cases in Cuba, and more than 5,000 likely should have been diagnosed and reported in 2017. The only difference was the timing. The Cuban outbreak of Zika virus occurred about a year after infections subsided elsewhere in the Caribbean.
To fill in more of the blanks, the researchers relied on Zika virus genomes from nine infected Florida travelers who returned from Cuba in 2017 and 2018. The sequencing data support multiple introductions of Zika virus to Cuba from other Caribbean islands in the summer of 2016.
The outbreak peaked about a year after the virus made its way to Cuba, similar to what happened in other places. But the Cuban outbreak was likely delayed by a year thanks to an effective mosquito control campaign by local authorities, following detection of the Brazilian outbreak. While information is lacking, including whether Zika infections had caused birth defects, it’s likely those efforts were relaxed once the emergency appeared to be over elsewhere in the Caribbean, and the virus took hold.
The findings serve as yet another reminder that the Zika virus—first identified in the Zika Forest in Uganda in 1947 and for many years considered a mostly inconsequential virus [4]—has by no means been eliminated. Indeed, such unrecognized and delayed outbreaks of Zika raise the risk of travelers innocently spreading the virus to other parts of the world.
The encouraging news is that, with travel surveillance data and genomic tools —enabled by open science—it is now possible to detect such outbreaks. By combining resources and data, it will be possible to develop even more effective and responsive surveillance frameworks to pick up on emerging health threats in the future.
In the meantime, work continues to develop a vaccine for the Zika virus, with more than a dozen clinical trials underway that pursue a variety of vaccination strategies. With the Zika pandemic resolved in the Americas, these studies can be harder to conduct, since proof of efficacy is not possible without active infections. But, as this paper shows, we must remain ready for future outbreaks of this unique and formidable virus.
References:
[1] Genomic epidemiology reveals multiple introductions of Zika virus into the United States. Grubaugh et al. Nature. 2017 Jun 15;546(7658):401-405.
[2] Travel surveillance and genomics uncover a hidden Zika outbreak during the waning epidemic. Grubaugh ND, Saraf S, Gangavarapu K, Watts A, Tan AL, Oidtman RJ, Magnani DM, Watkins DI, Palacios G, Hamer DH; GeoSentinel Surveillance Network, Gardner LM, Perkins TA, Baele G, Khan K, Morrison A, Isern S, Michael SF, Andersen .KG, et. al. Cell. 2019 Aug 22;178(5):1057-1071.e11.
[3] Mirroring the Zika epidemics in Cuba: The view from a European imported diseases clinic. Almuedo-Riera A, Rodriguez-Valero N, Camprubí D, Losada Galván I, Zamora-Martinez C, Pousibet-Puerto J, Subirà C, Martinez MJ, Pinazo MJ, Muñoz J. Travel Med Infect Dis. 2019 Jul – Aug;30:125-127.
[4] Pandemic Zika: A Formidable Challenge to Medicine and Public Health. Morens DM, Fauci AS. J Infect Dis. 2017 Dec 16;216(suppl_10):S857-S859.
Links:
Video: Uncovering Hidden Zika Outbreaks (Florida Gulf Coast University, Fort Myers)
Zika Virus (National Institute of Allergy and Infectious Diseases/NIH)
Zika Virus Vaccines (NIAID)
Zika Free Florida (Florida Department of Health, Tallahassee)
Grubaugh Lab (Yale School of Public Health, New Haven, CT)
Andersen Lab (The Scripps Research Institute, La Jolla, CA)
NIH Support: National Institute of Allergy and Infectious Diseases; National Center for Advancing Translational Sciences
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