Posted on by Dr. Francis Collins
There’s been much interest in using digital technology to help contain the spread of COVID-19 in our communities. The idea is to make available opt-in smart phone apps that create a log of other apps operating on the phones of nearby participants. If a participant tests positive for COVID-19 and enters the result, the app will then send automatic alerts to those phones—and participants—who recently came into close proximity with them.
In theory, digital tracing would be much faster and more efficient than the challenging detective work involved in traditional contract tracing. But many have wondered how well such an opt-in system would work in practice. A recent paper, published in the journal Nature, shows that a COVID-19 digital tracing app worked quite well in the United Kingdom .
The research comes from Christophe Fraser, Oxford University, and his colleagues in the U.K. The team studied the NHS COVID-19 app, the National Health Service’s digital tracing smart phone app for England and Wales. Launched in September 2020, the app has been downloaded onto 21 million devices and used regularly by about half of eligible smart phone users, ages 16 and older. That’s 16.5 million of 33.7 million people, or more than a quarter of the total population of England and Wales.
From the end of September through December 2020, the app sent about 1.7 million exposure notifications. That’s 4.4 on average for every person with COVID-19 who opted-in to the digital tracing app.
The researchers estimate that around 6 percent of app users who received notifications of close contact with a positive case went on to test positive themselves. That’s similar to what’s been observed in traditional contact tracing.
Next, they used two different approaches to construct mathematical and statistical models to determine how likely it was that a notified contact, if infected, would quarantine in a timely manner. Though the two approaches arrived at somewhat different answers, their combined outputs suggest that the app may have stopped anywhere from 200,000 to 900,000 infections in just three months. This means that roughly one case was averted for each COVID-19 case that consented to having their contacts notified through the app.
Of course, these apps are only as good as the total number of people who download and use them faithfully. They estimate that for every 1 percent increase in app users, the number of COVID-19 cases could be reduced by another 1 or 2 percent. While those numbers might sound small, they can be quite significant when one considers the devastating impact that COVID-19 continues to have on the lives and livelihoods of people all around the world.
 The epidemiological impact of the NHS COVID-19 App. Wymant C, Ferretti L, Tsallis D, Charalambides M, Abeler-Dörner L, Bonsall D, Hinch R, Kendall M, Milsom L, Ayres M, Holmes C, Briers M, Fraser C. Nature. 2021 May 12.
COVID-19 Research (NIH)
Christophe Fraser (Oxford University, UK)
Posted on by Dr. Francis Collins
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 , 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 , 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 , 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 . 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 .
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!
 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]
 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.
 Apple and Google partner on COVID-19 contact tracing technology. Apple news release, April 10, 2020.
 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.
 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.
Coronavirus (COVID-19) (NIH)
COVID-19, MERS & SARS (NIAID)
NIH Support: National Institute of Allergy and Infectious Diseases
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