COVID-19 Data Dispatch

Tag: superspreading

  • Sources and updates, April 10

    • Lessons learned from the non-superspreader Anime NYC convention: Last fall, one of the first Omicron cases detected in the U.S. was linked to the Anime NYC convention, a gathering of more than 50,000 fans. Many worried that the event had been a superspreader for this highly contagious variant, but an investigation from the CDC later found that, in fact, Omicron spread at the convention was minimal. My latest feature story for Science News unpacks what we can learn from this event about preventing infectious disease spread—not just COVID-19—at future large events. I am a big anime fan (and have actually attended previous iterations of Anime NYC!), so this was a very fun story for me; I hope you give it a read!
    • States keep reducing their data reporting frequency: Last Sunday, I noted that Florida—one of the first states to shift from daily to weekly COVID-19 data updates—has now gone down to updating its data every other week. This is part of an increasing trend, writes Beth Blauer from the Johns Hopkins COVID-19 data team in a recent blog post. “As of March 30, only eight states and territories (AR, DE, MD, NJ, NY, PA, PR, and TX) report case data every day of the week,” Blauer says. And it seems unlikely that states will increase reporting frequencies again without a major change in public health funding or the state of the pandemic.
    • Biden administration announces Long COVID task force: This week, the Biden administration issued a memo addressing the millions of Americans living with Long COVID. The administration is creating a new, interagency task force, with the goal of developing a “national research action plan” on Long COVID, as well as a report laying out services and resources that can be directed to people experiencing this condition. It’s worth noting that recent estimates from the U.K. indicate 1.7 million people in that country (or one in every 37 residents) are living with Long COVID; current numbers in the U.S. are unknown due to data gaps, but are likely on a similar scale, if not higher. 
    • New scientific data sharing site from the NIH: Not directly COVID-related, but an exciting new source: the National Institutes of Health (NIH) has created an online data repository for projects funded by and affiliated with the agency. The site currently includes over 100 datasets, including scientific data, genomic data, and clinical data; it also includes information on data management and sharing for researchers working on these projects. This press release from NIH has more info. (H/t Liz Essley Whyte.)
    • Study indicates continued utility for COVID-19 testing in schools: During the Omicron surge, testing programs in a lot of schools collapsed, simply because institutions didn’t have enough resources to handle all of the students and staff getting sick. The surge led some schools to consider whether school testing programs are worth continuing at all. But a new study, released last week in The Lancet, suggests that yes, surveillance testing can still reduce transmission—even when schools are dealing with highly contagious variants. (Note that this was a modeling study, not a real-world trial.)
    • Preprint shows interest in self-reporting antigen test results: Another interesting study released recently: researchers at the University of Massachusetts distributed three million free rapid, at-home antigen tests between April and October 2021, then studied how test recipients interacted with a digital app for ordering tests and logging results. About 8% of test recipients used the app, the researchers found; but more than 75% of those who used it did report their antigen test results to their state health agency. The results (which haven’t yet been peer-reviewed) suggest that, if institutions make it easy and accessible for people to self-report their test results, the reporting will happen.

    All featured sources

  • Five more things, February 20

    A few additional news items from this week:

    • Omicron has caused more U.S. COVID-19 deaths than Delta. Despite numerous headlines proclaiming the Omicron variant to be “milder” than previous versions of the coronavirus, this variant infected such a high number of Americans that it still caused more deaths than previous waves, a new analysis by the New York Times shows. Between the end of November and this past week, the U.S. has reported over 30 million new COVID-19 cases and over 154,000 new deaths, the NYT found, compared to 11 million cases and 132,000 deaths from August 1 through October 31 (a period covering the worst of the Delta surge).
    • 124 countries are not on target to meet COVID-19 vaccination targets. The World Health Organization (WHO) set a target for all countries worldwide to have 70% of their populations fully vaccinated by mid-2022. As we approach the deadline, analysts at Our World in Data estimated how many countries have already met or are on track to meet the goal. They found: 124 countries are not on track to fully vaccinate 70% of their populations, including the U.S., Russia, Bangladesh, Egypt, Ethiopia, and other large nations.
    • Anime NYC was not an omicron superspreader event, CDC says. In early December, the Minnesota health department sounded the alarm about a Minnesotan whose COVID-19 case had been identified as Omicron—and who had recently traveled to New York City for the Anime NYC convention. The CDC investigated possible Omicron spread at this event, both by contact tracing the Minnesota case and by searching public health databases for cases connected to the event. Researchers found that this convention was not a superspreader for Omicron, despite what many feared; safety measures at the event likely played a role in preventing transmission, as did the convention’s timing at the very beginning of NYC’s Omicron wave. I covered the new findings for Science News.
    • Americans with lower socioeconomic status have more COVID-19 risk, new paper shows. Researchers at Brookings used large public databases to investigate the relationship between socioeconomic status and the risk of COVID-19 infections or death from the disease. Their paper, published this month in The ANNALS of the American Academy of Political and Social Science, found that education and income are major drivers of COVID-19 risk, as are race and ethnicity. The researchers also found that: “ socioeconomic status is not related to preventative behavior like mask use but is related to occupation-related exposure, which puts lower-socioeconomic-status households at risk.” 
    • The federal government has failed to disclose how much taxpayers are spending for “free” COVID-19 tests. One month into the Biden administration’s distribution of free at-home COVID-19 tests to Americans who request them, millions have received those tests. But the government has not shared how much it spent for the tests, making it difficult for journalists and researchers to determine how much taxpayer money was paid for each testing kit. “The reluctance to share pricing details flies against basic notions of cost control and accountability,” writes KHN reporter Christine Spolar in an article about this issue. The government has also failed to share details about who requested these free tests or when they were delivered, making it difficult to evaluate how equitable this distribution has been.

    Note: this title and format are inspired by Rob Meyer’s Weekly Planet newsletter.

  • Three more COVID-19 data points, August 15

    Three more COVID-19 data points, August 15

    The number of children hospitalized with COVID-19 has shot up in recent weeks. Chart from the CDC COVID Data Tracker.

    A couple of additional items from this week’s COVID-19 headlines:

    • 1,900 children now hospitalized with COVID-19 in the U.S.: More kids are now seriously ill with COVID-19 than at any other time in the pandemic. The national total hit 1,902 on Saturday, according to HHS data. Asked about this trend at a press briefing on Thursday, Dr. Anthony Fauci explained that, thanks to Delta’s highly contagious properties, we’re now seeing more children get sick with COVID-19 just as we are seeing more adults get it. The vast majority of kids who contract the virus have mild cases, but this is still a worrying trend as schools reopen with, in many cases, limited safety measures. For more on this issue, I recommend Katherine J. Wu’s recent article in The Atlantic.
    • 2.7% of Americans now eligible for a third vaccine dose: Both the FDA and the CDC have now given the go-ahead for cancer patients, organ transplant recipients, and other immunocompromised Americans to get additional vaccine doses. There are about 7 million Americans eligible, comprising 2.7% of the population. Studies have shown that two Pfizer or Moderna doses do not provide these patients with sufficient COVID-19 antibodies to protect against the virus, while three doses bring the patients up to the same immune system readiness that a non-immunocompromised person would get out of two dioses. Still, this move goes against the World Health Organization’s push for wealthy nations to stop giving out boosters until the rest of the world has received more shots.
    • 203 cases so far linked to Lollapalooza, out of 385,000 attendees: Chicago residents and public health experts worried that Lollapalooza, a massive music festival held in the city in late July, would become a superspreader event. Two weeks out from the festival, however, local public health officials are seeing no evidence of superspreading, with a low number of cases identified in attendees. Lollapalooza may thus be an indicator that large events can still be held safely during the Delta surge—if events are held outdoors and the vast majority of attendees are vaccinated. (Officials estimated that 90% of the Lollapalooza crowd had gotten their shots.)

  • Was the Capitol invasion a superspreader event?

    Like everyone else, I spent Wednesday afternoon watching rioters attack the nation’s Capitol. I was horrified by the violence and the ease with which these extremists took over a seat of government, of course, but a couple of hours in, another question arose: did this coup spread COVID-19?

    The rioters came to Washington D.C. from across the country. They invaded an indoor space in massive numbers. They pushed legislators, political staff, and many others to hide in small offices for hours. They inspired heated conversations. And, of course, none of them wore masks. These are all perfect conditions for what scientists call a superspreading event—a single gathering that causes a lot of infections.

    (The number can vary, based on how you define a superspreading event; for more background, see this post from November.)

    My concerns were quickly echoed by many other COVID-19 scientists and journalists:

    The very next day, Apoorva Mandavilli published a story asking just this question in the New York Times. She quotes epidemiologists who point out that the event was ripe for superspreading among both rioters and Capitol Hill politicians. Many legislators were stuck together in small rooms, having arguments, while some of the Republican representatives refused to wear masks. POLITICO got a video of several Republicans refusing masks in a crowded safe room.

    By Friday, five Congressmembers had tested positive for COVID-19 in a week. It’s true, many of these legislators received vaccines in the first stage of the U.S. rollout in late December. But it takes several weeks for a vaccine to confer immunity, and we still don’t have strong evidence as to whether the Pfizer and Moderna vaccines prevent the coronavirus from spreading to other people. (They likely do, to some extent, but the evidence mainly shows that these vaccines prevent COVID-19 disease.)

    Just this morning, Punchbowl News’ Jake Sherman reported that the attending physician for Congress sent a note to all legislators and staff, warning them that “people in the safe room during the riots may have been exposed to the coronavirus.” I will be carefully watching for more reports of legislators testing positive in the coming weeks. From our nation’s previous experience with COVID-19 outbreaks at the White House, it seems unlikely that the federal government will systematically track these cases—though the incoming administration may change this. 

    As for the rioters themselves, while the events of January 6 may well have been superspreading, we likely will never know the true extent of this day’s impact. As I’ve written previously, we identify superspreading events through contact tracing, the practice of calling up patients to quiz them on their activities and help identify others who may have gotten sick. When case numbers go up—as they are now—it becomes harder to call up every new patient. One county in Michigan is so understaffed right now, it’s telling COVID-19-positive residents to contact trace themselves.

    But even if contact tracing were widely available in the communities to which those rioters are going home, can you really imagine them answering a phone call from a public health official? Much less admitting to an act of treason and risking arrest? No, these so-called patriots likely won’t even get tested in the first place.

    It would take rigorous scientific study to actually tie the Capitol riot to COVID-19 spread to the homes of the rioters. (That said, if you see a study like that in the months to come: please send it my way.)

    Finally, I have to acknowledge one more impact of the riot on D.C. at large: vaccine appointments were canceled after 4 PM that day. One of the most heinous aspects of that riot, to me, was how it pulled our collective attention away from the pandemic, precisely at a time when our collective health needs that attention most.

  • Your Thanksgiving could be a superspreading event

    Your Thanksgiving could be a superspreading event

    Between 10% and 20% of people infected with COVID-19 are responsible for 80% of the virus’ spread.

    You might have seen this statistic before, but take a second to think about what it means. Imagine that one unlucky person at a crowded restaurant, infected with the novel coronavirus but not yet symptomatic enough that she has noticed, spreads the virus to ten others. Meanwhile, her ten coworkers, who all contracted the virus at the same time as she did, do not spread the virus to anyone else at all. This type of dispersal—what epidemiologists call a large k value—introduces a level of randomness to COVID-19 spread which makes it difficult to track and protect against.

    But scientists are learning to better understand COVID-19 spread by keeping tabs on those instances where one person infects many, which they call superspreading events. While research continues about the underlying biology driving who is infectious and who isn’t, investigating the events in which people get infected can help us better understand how to protect ourselves and our communities.

    For more thorough explanations into the science of superspreading, I’d recommend you read Christie Aschwanden in Scientific American, Zeynep Tufekci in The Atlantic, or Martin Enserink, Kai Kupferschmidt, and Nirja Desai with an incredible series of scrolly visualizations in Science Mag.

    Here, I’m focusing on the data around these events: how we identify them, what the data tell us so far, and why we should keep them in mind as temperatures drop and cases rise.

    How do we find superspreading events?

    The CDC defines a superspreading event as one in which “a few persons infect a larger number of secondary persons with whom they have contact.” This leaves a lot of room for interpretation, as different researchers have different thresholds for determining how many people must be involved. Depending on who you talk to, anything from a 500-person rally to your extended family’s Fourth of July gathering might fit the definition.

    So, when you see a sensationalist article claiming that some event caused superspreading, it is important to consider what definition was being used and how the given event was identified as one that fits.

    There are three ways superspreading events can be identified:

    • Continuous tracking of an outbreak site: This is the easiest way to find superspreading. You have a place with a lot of people—say, a nursing home, a prison, a college campus—and you watch how many cases erupt over time. This may be an easier means of finding events because local administrations or public authorities are conducting regular testing and making data public; meanwhile, the sites themselves may have large groups of people living and working in close quarters, which is a prime environment for virus spread. Scientists count these sites as superspreading events even though they are not “events” in the way we usually think of the word because this type of long-term superspreading can have the biggest impact. California’s San Quentin State Prison, for example, was ordered to reduce its prison population after over 2,000 prisoners tested positive.
    • Contact tracing: This strategy, in which public health officials contact individuals who test positive and ask them about their contacts to find other infected individuals, has not taken off in the U.S. as it has in other countries, which makes it harder for us to identify superspreading events. It works like this: if contact tracers find that one new case is a teacher at an elementary school, for example, they can call other teachers and school administrators to find out which other cases are connected to that location. Japan has famously avoided widespread lockdowns by employing a “cluster-busting” strategy in which officials contact-trace backwards from new cases in order to find how those people got infected, then tell other people at the spreading events to isolate. Scientists in Europe and the U.S. are now promoting this approach as our cases surge.
    • Scientific studies: This strategy of superspreading identification is perhaps the least consistent, but it gets the most press. Epidemiologists may use publicly available case data, cell phone tracking data, or other information to look for patterns in new cases after major events. Such studies may draw attention, as a working paper on the Sturgis, South Dakota motorcycle rally did in September, but it can be difficult for scientists to investigate events when they don’t have access to data on precisely which cases are connected and how. The Sturgis paper was criticized for making estimates based on unreliable data. A similar new paper on the COVID-19 impact of Trump rallies is currently undergoing peer review.

    Where do superspreading events happen?

    Full-screen dashboard link.

    Independent researcher Koen Swinkels started a database to answer this question. The database is compiled from media reports, scientific papers, and public health dashboards, as well as volunteer reports. (You can submit an event through a form on the database’s site.)

    As of November 7, the database includes about 1,600 superspreading events, ranging from churches to dinner parties to meat processing plants. About 1,100 of these events took place in the U.S. For those American events, the most common superspreading settings by far are prisons (50,000 cases), rehabilitation/medical centers (27,000 cases), nursing homes (26,700 cases), meat processing plants (13,900 cases), and other medical centers (12,200 cases). Parts of the Northeast, West Coast, and South are heavily represented in the database, while other areas of the country have yet to see significant superspreading events logged.

    You can explore the map pictured above, as well as a bar chart which organizes superspreading settings by their COVID-19 case numbers, in a pair of interactive Tableau visualizations which I built based on this database.

    Swinkels emphasized in an email to me that the database is not at all representative of all COVID-19 superspreading events which have taken place, in America or around the world. “Hundreds of millions of people have been infected with SARS-CoV-2, while we have only about 200,000 cases linked to the 1,600 superspreading events in our database,” he said.

    He and other members of the team, including professors at the London School of Hygiene and Tropical Medicine, are currently compiling events from the most easily available public sources, which he admits is not a comprehensive strategy. Swinkels also noted that the events identified by public sources may be biased by where public health officials direct their focus, which can lead to settings that were closed in the spring or are now operating under restrictions being left out of this database and of superspreading research more broadly. The database is also biased by the team’s English-language familiarity; they are looking to find more events described in non-English language publications.

    What does this mean for the holidays?

    This newsletter topic was inspired by a reader question I got last week: Ross asked me how post-election gatherings and holiday celebrations might contribute to COVID-19 spikes.

    The evidence so far suggests that protests have not yet been a major cause of COVID-19 spikes. But “so far” is doing a lot of work in that sentence. While protests are generally outside and see high mask compliance, Swinkels explained, they tend to involve talking and singing in close contact, and instances of transportation and socialization around a protest might pose more risk. (Imagine, for example, shouting “FUCK TRUMP!” in a crowd of 500 with two friends, going to an outdoor bar together afterward, then each taking the bus home to three different parts of the city. That’s a lot of risk for one evening.)

    More research on protests is necessary to truly determine how much risk they might pose to the communities around them. And, as contact tracing apparatuses in different parts of the country scale up—slowly but surely—such research will get easier.

    Holiday celebrations, on the other hand, are a definitive cause for concern. These celebrations almost always occur indoors, involve talking and eating, and bring people together from disparate locations. Superspreader events also almost always occur indoors, may involve loud talking, and expand COVID-19 risk from one area to another. There’s a reason that Dr. Anthony Fauci’s daughters are not traveling home for Thanksgiving.

    I asked Koen what he’d learned from compiling and comparing hundreds of superspreader events. “Knowing more about where and when superspreading events occur can help you to avoid high-risk situations and live more freely in low-risk situations,” he said. He listed several key risk factors: indoors, poor ventilation, many people, close together, prolonged periods, loud vocalization (such as singing or shouting), and cold, dry air.

    He also highlighted the importance of understanding aerosol transmission. The six feet rule we’ve all come to know and flaunt is based on the dispersal of larger air particles, which don’t travel far from an infected person. But aerosols, which are smaller particles, are able to travel further and stay in the air longer—especially in indoor, poorly ventilated spaces. You can sit all the way across the room from Grandma while you eat, but if masks are off and all the windows are closed, it won’t make much difference. This FAQ document by aerosol scientists provides much more detail about how this type of COVID-19 spread works.

    I’m not going to tell you to avoid traveling for the holidays; I’m not a public health expert, I don’t have that authority. But I can give you this fact: your Thanksgiving could be a superspreading event. So could the train you take to get to your relatives’ house. So could the bar where you go for outdoor drinks a few days before traveling. In order to make it through this winter, we must all be aware of our risks and adjust our behavior accordingly.

  • Featured sources, Oct. 11

    As I promised in previous weeks, I’ve compiled all the data sources featured in this newsletter into a resource spreadsheet. The doc includes 56 sources, sorted by category (schools, testing, etc.) with descriptions and notes from past newsletters. I’ll keep adding to it in future weeks!

    (Editor’s note, Jan. 2: The resource list is now a page on this website.)

    • The Human Mortality Database: This database includes detailed population and mortality data for 41 countries. In response to the COVID-19 pandemic, the team behind the database has started compiling weekly death counts, which can be used for excess death calculations; they have compiled counts for 34 countries so far.
    • SARS-CoV-2 Superspreading Events: Superspreading events, or instances in which many people are infected with the novel coronavirus at once, have been identified as a major force behind the spread of COVID-19. This database includes over 1,400 superspreading events from around the world, with information on each event’s timing, location, inside/outside setting, and more.
    • COVID-19 Risk Levels Dashboard: A new map from the Harvard Global Health Institute and other public health institutions allows users to see the COVID-19 risk for every U.S. county. These risk levels are calculated based on daily cases per 100,000 population (7-day rolling average).
    • New York Times College and University COVID-19 counts: The NYT is now releasing the data behind its counts of COVID-19 cases reported on college and university campuses, which the paper has been collecting in surveys since July. The survey includes over 1,700 colleges. This initial data release only includes cumulative data as of September 8—and it does not include denominators. NYT reports that the data will be updated “approximately every two weeks.”
    All featured sources