COVID-19 Data Dispatch

Category: Long COVID

  • Five reasons why Long COVID research in the U.S. is so difficult

    Five reasons why Long COVID research in the U.S. is so difficult

    Medical and research institutions participating in the NIH’s Long COVID study are, unsurprisingly, concentrated in states with more scientific resources. Chart via Grid; see the full story for the interactive version!

    In December 2020, Congress provided the National Institutes of Health (NIH) with over $1 billion to study Long COVID. A couple of months later, the agency announced it would use this funding for an initiative called RECOVER: a large clinical trial aiming to enroll 40,000 patients, designed to answer long-standing questions about Long COVID and, eventually, identify potential treatments.

    At the time, Long COVID patients and researchers were thrilled to see this massive investment. Long COVID patients may suffer from hundreds of possible symptoms, many of them debilitating; reports estimate that millions of people are out of work as a result of the condition. To anyone who has experienced Long COVID or talked to patients, as I have in my reporting, it’s clear that we need treatment options, and we need them yesterday.

    But that promising NIH study is floundering: it’s moving incredibly slowly (with treatment trials potentially years off); it’s enrolled a tiny fraction of the 40,000 patients originally planned; it’s failing to meet the needs of patients from the communities most vulnerable to COVID-19; and it has been critiqued by patient advocates on concerns of trial setup, transparency, engagement, inclusion of other post-viral illnesses, and more.

    I explored the concerns around RECOVER for a story in Grid, published last Monday. My piece highlights critiques from patient advocates and Long COVID researchers outside of RECOVER, while also discussing some of the broader problems that make it difficult for an initiative like this to succeed in the first place.

    In the COVID-19 Data Dispatch today, I’d like to dig deeper into those broader problems and share some material from my reporting for the Grid story that didn’t make it into the final piece. Here are five reasons why the U.S. is not set up for success when it comes to Long COVID research, based on my interviews and research for the piece.

    The NIH is designed for stepwise research, not “disruptive innovation.”

    One of my favorite quotes in the story comes from David Putrino, who directs a lab at Mount Sinai focused on health innovations and was one of the first scientists in the U.S. to begin focusing on Long COVID. Putrino described how the NIH’s usual mode of operation does not work when it comes to novel conditions like Long COVID:

    “What the NIH does very well, better than most national research organizations around the world, is supporting research that slowly develops small innovations in scientific knowledge,” Putrino said. The agency normally supports series of stepwise trials, climbing from one tiny aspect of research into a condition or treatment to the next.

    This method is good for “long-term innovations that take 20 years,” Putrino said, but not for “disruptive innovation.” Treatments for long covid fall into the latter category: higher-risk, higher-reward science that may be viewed as a waste of government funding if it doesn’t pay off.

    The same day as my Grid story was published, last Monday, STAT News published a story by Lev Facher discussing an oversight board at the NIH that was supposed to improve efficiency at the agency… and has not met for seven years. While this story doesn’t discuss Long COVID specifically, it provides some pretty clear context for why a study like RECOVER—which is different from anything the agency has done before—may be hard to get off the ground.

    Here’s the final quote in Facher’s story, from Robert Cook-Deegan, founding director of the Duke Center for Genome Ethics, Law and Policy:

    “About every 10 years, the National Academies [of Sciences, Engineering, and Medicine] are asked to review NIH, and they make recommendations, most of which are ignored,” he said. The agency’s “large, inertial, and ponderous bureaucracy,” he added, is “not terribly open to criticism as a whole.”

    Clinical trials are difficult and time-consuming to set up, especially when they involve new drugs.

    My story also discusses the red tape that U.S. researchers face when they attempt to test potential treatments on human subjects. For such a clinical trial, researchers need to get approval from an Institutional Review Board (or IRB), an oversight board that ensures a study’s design protects the rights and welfare of people who participate in the trial.

    In the U.S., this approval can take months, and may have extra steps for government-funded research. Researchers in other countries often have much shorter processes, Lauren Stiles, president of the research and advocacy organization Dysautonomia International, told me. She gave the example of a researcher in Sweden studying a potential Long COVID treatment with funding from her organization: for this researcher, the equivalent of IRB approval took a few hours rather than a few months.

    Clinical trials in the U.S. also face extra hurdles when they involve studying new drugs, as our research system makes it easier for companies that develop these drugs to do new clinical trials than for outside academics to undertake similar studies. For example, Putrino told me that he would love to study the potential for Paxlovid, the antiviral drug for acute COVID-19, to treat Long COVID patients. But, he said, “I physically don’t have the bandwidth to fill out the hundreds of pages of documents” that would be required for such a trial.

    A recent story in The Atlantic from Katherine J. Wu focuses further on Paxlovid’s potential as a Long COVID treatment—and how hard it is to study. Quoting from Wu:

    The company is “considering how we would potentially study it,” Kit Longley, a spokesperson for Pfizer, wrote in an email, but declined to clarify why the company has no study under way. That frustrates Putrino, of Mount Sinai, who thinks Pfizer will need to spearhead many of these efforts; it’s Pfizer’s drug, after all, and the company has the best data on it, and the means to move it forward… When asked to elaborate on Paxlovid’s experimental status, the NIH said only that the agency “is very interested in long term viral activity as a potential cause of PASC (long COVID), and antivirals such as Paxlovid are in the class of treatments being considered for the clinical trials.”

    The NIH has historically underfunded and undervalued research into other post-viral conditions.

    When I shared my Grid story on Twitter this week, a lot of patients with myalgic encephalomyelitis (ME), dysautonomia, and other post-viral illnesses said that the issues outlined in my piece felt very familiar.

    https://twitter.com/sshabein/status/1524114628740993024

    After all, the NIH has been failing to fund research into their conditions for decades. Pots, one type of dysautonomia, received less than $2 million a year in NIH funding before the pandemic, Stiles told me. As a result, scientists and clinicians in the U.S. have fairly limited information on these other chronic conditions—in turn, limiting the sources that Long COVID researchers may use as starting points for their own work.

    Long COVID patients share a lot of symptoms with ME, dysautonomia, and other chronic post-viral illness patients; in fact, many Long COVID patients have been diagnosed with these other conditions. According to one study by the Patient-Led Research Collaborative, almost 90% of Long COVID patients experience post-exertional malaise, the most common symptom of ME.

    Despite the historical underfunding, post-viral illness researchers have still made major strides in studying this condition that could provide springboards for RECOVER. But the NIH trial isn’t using them, say experts I talked to. Here are a few paragraphs from an early draft of the story:

    “NIH is approaching Long COVID as a brand-new phenomenon,” said Emily Taylor, an advocate at Solve ME, even though it has extensive overlaps with these other conditions. “We’re starting at square one, instead of starting at square 100.”

    Long COVID patients and those ME have already come together organically to share tips and resources, she said. For example, Long COVID patients versed in medical research have educated ME patients on potential biological mechanisms for their chronic illness, while ME patients have shared methods for resting, pacing, and managing their conditions.

    Experts in conditions like ME were not included in the trial’s leadership early on, and are now outnumbered in committees by cardiologists, respiratory experts, and others who have limited existing knowledge about post-viral illness. “Right now, there are three people with [dysautonomia] expertise on these committees,” Stiles said.

    With the other two experts, Stiles has advocated for autonomic testing—a series of tests measuring the autonomic nervous system, believed to be a key driver of Long COVID symptoms—to be conducted on all RECOVER patients. A few of these tests have been added to the protocol, she said, but not the full list needed to get a comprehensive reading of patients’ nervous systems.

    America’s fractured medical system and lack of broad knowledge on Long COVID have contributed to data gaps, access issues.

    How does a Long COVID patient know that they have Long COVID? Ideally, more than two years into the pandemic, the U.S. medical system would have developed a consistent way of diagnosing the condition. Instead, patients are still getting diagnoses in a variety of ways, including (but not limited to):

    • A positive PCR test, followed by prolonged symptoms.
    • A positive rapid/at-home test, followed by prolonged symptoms.
    • Prolonged symptoms, perhaps later associated with COVID-19 via a positive antibody test.
    • Self-diagnosis based on prolonged symptoms.
    • An official diagnosis of Long COVID from a doctor.
    • An official diagnosis of ME, pots, mass cell activation syndrome, and/or other conditions from a doctor.

    Patients also continue to face numerous barriers to formal Long COVID diagnoses, compounded by the fractured nature of the medical system. A lot of doctors and other medical providers—especially at the primary care level—still don’t know about the condition, and may make it hard for patients to learn that their prolonged fatigue is actually Long COVID. PCR or lab-based COVID-19 testing is also getting harder to access across the country, and many doctors won’t take a positive antigen test as proof of infection.

    All of this means that the U.S. does not have a good estimate of how many Americans are actually suffering from Long COVID. There’s no central registry of patients who can be contacted for potential trials; there aren’t even basic demographic estimates of how many Long COVID patients are Black, Hispanic, or otherwise from marginalized communities. These data gaps make it hard for researchers studying Long COVID to set goals for patient recruitment.

    And then, beyond receiving a diagnosis, actually getting care for Long COVID may require patients to wait weeks for appointments with specialists, contact many different doctors, and generally advocate for themselves in the medical system—while dealing with chronic, debilitating symptoms. As a result, as I wrote in the story:

    The long covid patients who are believed by their doctors, who garner media attention, who serve on RECOVER committees — they’re more likely to be white and financially better-off, said Netia McCray, a Black STEM entrepreneur and long covid patient who has enrolled in the trial.

    So far, RECOVER has not been doing much to combat this inherent bias in the patients who know about the trial (and about their own condition) and are able to sign up for participation.

    Clinical trials in the U.S. are not typically set up in a way that prioritizes patient engagement, especially chronically ill patient engagement.

    One major concern from Long COVID patient advocates involved with RECOVER is that the trial has not prioritized patient engagement—which should be a priority, considering all the medical bias that patients have faced while they’ve become experts in their own condition over the last two years.

    Here’s a bit more detail on this issue, taken from an early draft of my Grid story:

    Patients serving on the committees are dramatically outnumbered by scientists, creating an “intimidating” environment that makes it hard to speak up about their needs, said Karyn Bishof, founder of the COVID-19 Longhauler Advocacy Project. This feeling is exacerbated when scientists on the committees are misinformed about Long COVID and dismiss patients’ experiences, she said.

    Some scientists on the committees are receptive to patient input, representatives told me. Still, the structure is not in their favor: not only are patents outnumbered, it’s also a challenge for them to simply show up to committee meetings. Many Long COVID patients are, by definition, dealing with chronic symptoms that are not conducive to regular meeting attendance. Some are managing a barrage of doctors appointments, jobs, caregiving responsibilities, and more.

    For instance, a second patient representative on a committee with Lauren Stiles—who serves as a representative because she has suffered from Long COVID in addition to other forms of dysautonomia—once missed a meeting because she had to go to the hospital. “If I wasn’t there, no patient would have been represented at all,” Stiles said.

    Patients are compensated for their time in meetings, but not for hours spent doing other research outside those calls. And there’s no structure for patient representatives to coordinate more broadly; patients are operating in silos, with limited information about what representatives on other committees may be doing.

    The NIH has potential models for improving this structure; it could draw from past HIV/AIDS clinical trials that had oversight from that patient community, advocate JD Davids told me. And leaders of RECOVER have acknowledged that they need to improve: as I highlighted in the story, trial leadership met with patient advocates earlier this month to discuss potential changes:

    [Lisa McCorkell, advocate and researcher from the Patient-Led Research Collaborative] said that the meeting made it clear that the NIH and RECOVER leadership understand that improving patient engagement is key to the study’s success. “We agreed to work together to strengthen trust, improve representation of patients, and ensure greater accountability and transparency,” she said in an emailed statement.

    The pressure is on for the NIH and RECOVER leadership to follow up on their promises. I, for one, intend to continue reporting on the trial (and on Long COVID research more broadly) as much as possible.

    More Long COVID reporting

  • COVID source shout-out: U.K. Long COVID estimates

    COVID source shout-out: U.K. Long COVID estimates

    About 1.7 million people in the U.K. were experiencing self-reported Long COVID as of early March, according to the U.K. Office of National Statistics.

    I spent a lot of time this weekend talking about the U.S.’s lack of Long COVID data, particularly our inability to answer such questions as, “How many Americans have Long COVID?” and, “What is the condition’s demographic breakdown?”

    In comparison, I pointed other journalists to reports from the U.K.’s Office for National Statistics. This office regularly surveys Brits on their Long COVID experiences, asking a representative sample of the population whether they are experiencing any long-term COVID-19 symptoms.

    The most recent report, published in early April, found that about 1.7 million people—or 2.7% of the U.K.—was “experiencing self-reported long COVID” (defined as symptoms persisting for four weeks or more after an initial infection). Imagine what the scale of Long COVID might be in the U.S.

    A new report is coming this week, on May 6.

    more source spotlights

  • Sources and updates, April 24

    • COVID-19 and public transportation: This week’s biggest COVID-19 news story was, without a doubt, a Florida judge striking down the U.S.’s mask mandate for public transportation (including airplanes, trains, buses, and terminals for all these transit methods). The federal justice department is appealing the decision, as the CDC has determined that masks are still necessary in these settings—at least, while the BA.2 surge is at large. Two good articles to read on this topic: Your Local Epidemiologist’s explanation of coronavirus transmission risk on planes, and Slate’s rundown of what this judge’s ruling could mean for future infectious disease outbreaks.
    • Hospitalizations of young children during Omicron: A major study released in the CDC’s Morbidity and Mortality Weekly Report (MMWR) this week describes hospitalization rates among children ages five to 11, focusing on the Omicron wave in December through February. Findings include: about nine in ten of the children hospitalized during this period were unvaccinated, and hospitalization rates were twice in high in unvaccinated children compared to vaccinated children, demonstrating the importance of vaccination in the five to 11 age group.
    • COVID-19 death rates by race and ethnicity: Another notable study published in MMWR this week: CDC researchers used provisional mortality data (based on death certificates) to study COVID-19 death rates among different racial and ethnic groups, comparing 2020 and 2021. Death rates for Hispanic, Black, and Native Americans were closer to the rates for white Americans in 2021 than they had been in 2020, the report found; this is likely tied to lower vaccination rates and, consequently, higher death rates in conservative and rural areas. For any reporters seeking to investigate these patterns in their regions, the Documenting COVID-19 project’s CDC mortality data repository includes county-level death data from the same source as this MMWR report.
    • New CMS data on hospital and nursing home ownership: Nursing homes and other long-term care facilities have been under increased scrutiny during the pandemic, as COVID-19 revealed major flaws in facilities’ ability to care for vulnerable seniors, A series of new datasets from the Centers of Medicare & Medicaid Services (CMS) aims to enable more scrutiny: the datasets include changes of ownership for skilled nursing facilities and for hospitals. CMS plans to update these datasets on a quarterly basis, according to a press release about the new data.
    • New funding for patient-led Long COVID research: The Patient-Led Research Collaborative (PLRC), a group of Long COVID patients that have produced leading research on their condition, announced this week that they’ve received $3 million in funding. This funding comes from Balvi, a fund for high-impact COVID-19 projects established by Ethereum co-creator Vitalik Buterin. PLRC announced that $2 million will go to start a pool of Long COVID research grants—to be awarded directly by patients—while the remaining $1 million will fund a series of PLRC-led studies. I look forward to reporting on the results of this research! (Also, related: this week, I updated the source list of Long COVID patients and experts willing to talk to reporters, which I compiled with Fiona Lowenstein.)
    • FDA authorizes breathalyzer for COVID-19: The latest new COVID-19 test is a breathalyzer: this machine, developed by Texas-based diagnostics company InspectIR,  analyzes chemicals in a person’s breath to quickly detect compounds signifying a coronavirus infection. This test can deliver results in just three minutes—even faster than an antigen test—but it needs to be performed in a medical setting; InspectIR is working on a version that could be hand-held, like breathalyzers for alcohol. Impressive as the technology is, this data reporter is asking: how will those test results get reported to public health agencies?

    All featured sources

  • 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
  • All the U.S.’s COVID-19 metrics are flawed

    All the U.S.’s COVID-19 metrics are flawed

    This week, I had a big retrospective story published at FiveThirtyEight: I looked back at the major metrics that the U.S. has used to track COVID-19 over the past two years—and how our country’s fractured public health system hindered our use of each one.

    The story is split into seven sections, which I will briefly summarize here:

    • Case counts, January to March 2020: Early on in the pandemic, the U.S. had a very limited picture of COVID-19 cases due to our very limited testing: after rejecting a test made by the WHO, the CDC made its own test—which turned out to have contamination issues, further slowing down U.S. testing. In early March 2020, for example, the majority of cases in NYC were identified in hospitals, suggesting that official counts greatly underestimated the actual numbers of people infected.
    • Tests administered, March to September 2020: Test availability improved after the first wave of cases, with organizations like the COVID Tracking Project keeping a close eye on the numbers. But there were a lot of challenges with the testing data (like different units across different states) and access issues for Americans with lower socioeconomic status.
    • Hospitalizations, October to December 2020: By late 2020, many researchers and journalists were considering hospitalizations to be a more reliable COVID-19 metric than cases. But it took a long time for hospitalization data to become reliable on a national scale, as the HHS launched a new tracking system in the summer and then took months to work out kinks in this system.
    • Vaccinations, January to June 2021: When the vaccination campaign started in late 2020, it was “tempting to forget about all other COVID-19 metrics,” I wrote in the story. But the U.S.’s fractured system for tracking vaccinations made it difficult to analyze how close different parts of the country were to prospective “herd immunity,” and distracted from other public health interventions that we still needed even as people got vaccinated.
    • Breakthrough cases, July to November 2021: The Delta surge caused widespread infections in people who had been vaccinated, but the CDC—along with many state public health agencies—was not properly equipped to track these breakthrough cases. This challenge contributed to a lack of good U.S. data on vaccine effectiveness, which in turn contributed to confusion around the need for booster shots.
    • Hospitalizations (again), December to January 2022: The Omicron surge introduced a need for more nuance in hospitalization data, as many experts asked whether COVID-19 patients admitted with Omicron were actually hospitalized for their COVID-19 symptoms or for other reasons. Nuanced data can be useful in analyzing a variant’s severity; but all COVID-related hospitalizations cause strain on the healthcare system regardless of their cause.
    • New kinds of data going forward: In our post-Omicron world, a lot of public health agencies are shifting their data strategies to treat COVID-19 more like the flu: less tracking of individual cases, and more reliance on hospitalization data, along with newer sources like wastewater. At this point in the pandemic, we should be fortifying data systems “for future preparedness,” I wrote, rather than letting the systems we built up during the pandemic fall to the wayside.

    I did a lot of reporting for this piece, including interviews with some of the U.S.’s foremost COVID-19 data experts and communicators. As long as the piece is, there were a lot of metrics (and issues with these metrics) that came up in these interviews that I wasn’t able to include in the final story—so I wanted to share some bonus material from my reporting here.

    Long COVID:

    As I’ve discussed in previous issues, the U.S. has done a terrible job of collecting data on Long COVID. The NIH estimates that this condition follows a significant share of coronavirus infections (between 10% and 30%), but we have limited information on its true prevalence, risk factors, and strategies for recovery.

    Here’s Dr. Eric Topol, the prolific COVID-19 commentator and director of the Scripps Research Translational Institute, discussing this data problem:

    [Long COVID has] been given very low priority, very little awareness and recognition. And we have very little data to show for it, because it hasn’t been taken seriously. But it’s a very serious matter.

    We should have, early on, gotten at least a registry of people —a large sample, hundreds of thousands of people prospectively assessed, like is being done elsewhere [in the U.K. and other countries]. So that we could learn from them: how long the symptoms lasted, what are the symptoms, what are the triggers, what can be done to avoid it, the role of vaccines, the role of boosters, all this stuff. But we have nothing like that.

    The NIH’s RECOVER initiative may answer some of these questions, but it will take months—if not years—for the U.S. to actually collect the comprehensive data on Long COVID that we should have started gathering when the condition first began gaining attention in 2020.

    Demographic data:

    In the testing section of the story, I mention that the U.S. doesn’t provide much demographic data describing who’s getting tested for COVID-19. There is actually a little-known provision in the CARES Act that requires COVID-19 testing providers to collect certain demographic data from all people who seek tests. But the provision is not enforced, and any data that are collected on this subject aren’t making it to most state COVID-19 dashboards, much less to the CDC’s public data dashboard.

    Here’s Dr. Ellie Murray, an epidemiologist at the Boston University School of Public Health, discussing why this is an issue:

    We don’t collect reason for seeking a test. We don’t collect age, race, ethnicity, occupation of people who seek a test. Those kinds of things could provide us with some really valuable information about who is getting tested, when, and why—that could help us figure out, what are the essential occupations where people are having a lot of exposures and therefore needing to get a lot of tests? Or are there occupations where we’re seeing a lot of people end up in hospital, who have those occupations, but they’re not getting tests, because actually, the test sites are nowhere near where they need to work, or they don’t have the time to get there before they close.

    And so we don’t really know who is getting tested, and that, I think, is a bigger problem, than whether the numbers that are being tested tell us anything about the trajectory of COVID. Because we have case data, and hospitalization data, and death data to tell us about the trajectory. And the testing could really tell us more about exposure, and concern, and access—if we collected some more of this data around who is getting tested and why.

    Test positivity:

    Speaking of testing: another metric that I didn’t get into much in the story was test positivity. Test positivity—or, the share of COVID-19 tests that return a positive result—has been used from the CDC to local school districts as a key metric to determine safety levels. (For more on this metric, check out my FAQ post from this past January.)

    But even when it’s calculated correctly, test positivity faces the same challenges as case data: namely, bias in who’s getting tested. Here’s Lauren Ancel Meyers, director of the University of Texas at Austin’s COVID-19 Modeling Consortium, explaining this:

    Test positivity is just as fraught [as cases]. It’s just as difficult, because you need to know the numerator and the denominator—what’s influencing the numerator and the denominator? Who is going to get tested, who has access to tests? … It used to be, at the very beginning [of the pandemic], nobody could get a test who wanted a test. And now, today, everybody has a test in their medicine cabinet, and they don’t get reported when they test. It’s different issues that have ebbed and flowed throughout this period.

    Often, if you’re a good data analyst or a modeler, and you have all the information, you can handle those kinds of biases. But the problem is, we don’t know the biases from day to day. And so even though there are statistical tools to deal with incomplete bias, without knowing what those biases are, it’s very hard to do reliable inference, and really hard to understand what’s actually going on.

    Genetic surveillance:

    Also related to testing: genetic surveillance for coronavirus variants of concern. Genetic surveillance is important because it can help identify new variants that may be more transmissible or more likely to evade protection from vaccines. It can additionally help track the qualities of concerning variants once they are identified (if variant data is linked to hospitalization data, vaccination data, and other metrics—which is not really happening in the U.S. right now.)

    Our current genetic surveillance systems have a lot of gaps. Here’s Leo Wolansky, from the Rockefeller Foundation’s Pandemic Prevention Institute (PPI), discussing how his organization seeks to address these challenges:

    [We’re trying to understand] where our blind spots are, and the bias that we might experience with a lot of health system reporting. One of the things that PPI has been doing is identifying centers of excellence in different parts of the world that can improve the sequencing of new cases in underrepresented countries. And so for example, we’ve provided quite a bit of support to the folks in South Africa that ultimately rang the alarm on Omicron.

    We’re also doing this by actually trying to systematically assess countries’ capacity for this type of genomic surveillance. So thinking about, how many tests have been recorded? What’s that test positivity rate? Do we have confidence in the basic surveillance system of the country? And then, do we also see enough sequences, as well as sequencing facility data, to demonstrate that this country can sequence and just isn’t doing enough—or cannot sequence because it needs foundational investment in things like laboratories and devices. We’ve been mapping this capacity just to make sure that we understand where we should be investing as a global community.

    The Pandemic Prevention Institute is taking a global perspective in thinking about data gaps. But these gaps also exist within the U.S., as is clear when one looks at the differences in published coronavirus sequences from state to state. Some states, like Wyoming, Vermont, and Colorado, have sequenced more than 10% of their cumulative cases, according to the CDC. Others, like Oklahoma, Iowa, and South Dakota, have sequenced fewer than 3%. These states need additional investment in order to thoroughly monitor coronavirus transmission among their residents.

    Cohort studies:

    In a cohort study, researchers follow a group of patients over time in order to collect long-term data on specific health conditions and/or the outside factors that influence them. The U.S. has set up a few cohort studies for COVID-19, but they haven’t been designed or utilized in a way that has actually provided much useful data—unlike cohort studies in some other countries. (The U.K., for example, has several ongoing cohort studies collecting information on COVID-19 symptoms, infections in schools, seroprevalence, and more.)

    Here’s Dr. Ellie Murray explaining the lost potential of these studies in the U.S.:

    There are a number of existing cohort studies that have been asked or who asked to pivot to collecting COVID information and therefore collecting long-term COVID information on their cohorts. But there doesn’t seem to be any kind of system to [determine], what are the questions we need answered about COVID from these kinds of studies? And how do we link up people who can answer those questions with the data that we’re collecting here, and making sure we’re collecting the right data? And if this study is going to answer these questions, and this one is going to answer those questions—or, here’s how we standardize those two cohorts so that we can pull them together into one big COVID cohort.

    And so, we end up in this situation where, we don’t know what percent of people get Long COVID, even though we’ve been doing this for over two years. We don’t even really know, what are all the different symptoms that you can get from COVID? … There are all these questions that we could be sort-of systematically working our way through, getting answers and using them to inform our planning and our response. [In addition to having] standardized questions, you also need a centralized question, instead of just whatever question occurs to someone who happens to have the funding to do it.

    Excess deaths:

    Excess deaths measure the deaths that occur in a certain region, over a certain period of time, above the number of deaths that researchers expect to see in that region and time period based on modeling from past years’ data. Excess deaths are the COVID-19 metric with the longest lag time: it takes weeks from initial infection for someone to die of the disease, and can take weeks further for a death certificate to be incorporated into the public health system.

    Once that death information is available, however, it can be used to show the true toll of the pandemic—analyzing not just direct COVID-19 deaths, but also those related to isolation, financial burden, and other indirect issues—as well as who has been hit the hardest.

    Here’s Cecile Viboud, a staff scientist at the NIH who studies infectious disease mortality, discussing this metric:

    We’ve been using the excess death approach for a long time. It comes from flu research, basically starting in 1875 in the U.K. And it was used quite a lot during the 1918 pandemic. It can be especially good in examining historical records where you don’t have lab confirmation—there was no testing ability back in those days…

    So, I think it’s kind of natural to use it for a pandemic like COVID-19. Very early on, you could see how useful this method was, because there was so little testing done. In March and April 2020, you see substantial excess, even when you don’t see lab-confirmed deaths. There’s a disconnect there between the official stats, and then the excess mortality… [We can also study] the direct effect of COVID-19 versus the indirect effect of the pandemic, like how much interventions affected suicide, opioids, death, accidents, etc. The excess approach is also a good method to look at that.

    Viboud also noted that excess deaths can be useful to compare different parts of the U.S. based on their COVID-19 safety measures. For example, one can analyze excess deaths in counties with low vaccination rates compared to those with high vaccination rates. This approach can identify the pandemic’s impact even when official death counts are low—an issue that the Documenting COVID-19 project has covered in-depth.

    Again, you can read the full FiveThirtyEight story here!

    More federal data

  • Sources and updates, March 6

    A couple of data sources, a couple of data-related updates:

    • State plans for utilizing COVID-19 relief funding: The federal Office of Elementary and Secondary Education has posted every state’s plan for utilizing ESSER funding, a $13-billion fund set aside to help schools address the impact of COVID-19. Money can be utilized for academic assistance, improving ventilation in schools, testing, and more. State plans were due to the federal government last June, though some materials are still pending on the website.
    • New GAO report on Long COVID: Between 8 and 23 million Americans may have developed Long COVID in the last two years—and an estimated one million are out of work because of this condition—according to a new report from the U.S. Government Accountability Office. The report discusses medical and economic impacts of Long COVID, including current efforts by the federal government to study the condition.
    • KFF COVID-19 Vaccine Monitor update: This week, the Kaiser Family Foundation published a new report detailing America’s sentiments on COVID-19 vaccines and other pandemic issues. Key findings include: COVID-19 vaccine uptake “remains relatively unchanged since January” for both adults and children; a majority of parents with children under five say they “don’t have enough information” about vaccines for that age group; and “most adults believe that the worst of the COVID-19 pandemic is over but there are disagreements about what returning to normal means and when it should happen.”
    • Vaccination disparities between urban and rural counties: Here’s a CDC MMWR study that caught my eye this week: researchers compared vaccination rates in urban and rural U.S. counties, finding that the rate of people in urban counties who have received at least one dose (75.4%) is much higher than the rate in rural counties (58.5%). Moreover, the gap between urban and rural counties has more than doubled between April 2021 and January 2022, the researchers found.
    • CDC updates seroprevalence data: The CDC recently updated a dashboard showing data from seroprevalence surveys, which use information from labs across the country to estimate how many Americans have resolving or recent coronavirus infections. (This does not include vaccinations, unlike other seroprevalence estimates.) According to this new update, about 43% of the country had antibodies from a recent infection as of late January. In some parts of the country that were harder-hit by Omicron, the esimate is over 50%.

    All featured sources

  • Sources and updates, February 13

    • Biden administration is reportedly shifting hospital reporting on COVID-19 patients: During the Omicron surge, there’s been a push among some COVID-19 experts (and in the media) to separately report patients who are admitted to hospitals because of their COVID-19 symptoms from patients who are admitted to hospitals for some other reason, but then test positive later. This push, also called the “with” versus “for” issue, has reached the White House, according to a recent report from POLITICO. The Biden administration now wants all hospitals to separate out their COVID-19 numbers in this way, to get a better picture of severe disease caused by the virus. Such a shift may be tricky for hospitals to follow, however, in part because a lot of people who appear to be incidental, “with COVID-19” patients actually had rare symptoms or chronic conditions exacerbated by the virus. “You need a panel of experts to review the cases” and judge this issue, expert Eric Topol told POLITICO.
    • Long-term cardiovascular outcomes of COVID-19: A new paper from researchers at the Department of Veterans Affairs (VA), published this week in Nature Medicine, sheds light on potential long-term COVID-19 impacts for the heart. The researchers used national health records databases from the VA to study over 150,000 COVID-19 patients—a much larger study size than most Long COVID research in the U.S. The paper found that, after their first month of infection, COVID-19 patients are at increased risk for a variety of cardiovascular issues, including heart inflammation and heart failure. Outside scientists commenting on the paper in Science magazine said that the findings clearly demonstrate that COVID-19 has grave long-term risks for heart health.

    All featured sources

  • Three more things, January 30

    A couple of additional news items for this week:

    • Two House Democrats called on the CDC to release more Long COVID data. This week, Rep. Ayanna Pressley (from Massachusetts) and Rep. Don Beyer (from Virginia) sent the CDC a letter insisting that the agency report estimates of Long COVID infection numbers, including demographic breakdowns by race, gender, and age. “Collecting and publishing robust, disaggregated demographic data will help us better understand this illness and ensure that we are targeting lifesaving resources to those who need them most,” said Rep. Pressley in a statement to the Washington Post. While studies that may, theoretically, help provide such data are in the works via the National Institutes of Health’s RECOVER consortium, the consortium has yet to release any results. Long COVID continues to represent one of the biggest COVID-19 data gaps in the U.S.
    • We don’t know yet whether cannabis can treat COVID-19, despite promising early studies. Recent studies have shown that CBD, along with other products containing marijuana and hemp, has some capacity to block coronavirus spread in the body in lab-grown cells and in mice. The studies were quickly turned into sensationalist headlines, even though it’s too early to say whether these products could actually be used to treat COVID-19. An excellent STAT News article by Nicholas Florko and Andrew Joseph describes the studies and their limitations, as well as how these early reports of COVID-19 treatment potential are “adding to the FDA’s existing CBD headache” when it comes to regulating these products.
    • Have you received your free at-home rapid tests from the USPS yet? Last week, I described the federal government’s effort to distribute at-home rapid tests to Americans free of charge, along with the equity issues that have come with this initiative so far. This week, I saw some reports on social media indicating that people have started receiving their tests! Have you gotten your tests yet? If you have, I would love to hear from you—in absence of formal data from the USPS, maybe we can do some informal data collection on test shipping times within the COVID-19 Data Dispatch community.

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

  • A new resource for journalists covering Long COVID

    A new resource for journalists covering Long COVID

    Screenshot of the source list, showing some of the main how-to info available.

    This week, a new resource that I’ve been working on for the past few months went live: a comprehensive source list including Long COVID patients and experts who are willing to talk to reporters. This source list project was a collaboration with Fiona Lowenstein, who’s a journalist, speaker, consultant, and founder of the Body Politic support group for Long COVID patients.

    Here’s some info about the source list:

    • It includes over 300 Long COVID sources from the U.S. and other countries, spanning all ages, race and ethnicity groups, and other demographics.
    • It’s sorted into four categories: patients who identify as Long COVID experts and/or advocates; patients who aren’t experts but can speak to their own lived experience; other experts (scientists, clinicians, advocates, etc.); and related conditions and experiences.
    • Patients and experts have identified topics about which they’d like to talk to journalists, including Long COVID research, patient care, policy, mental health, relationships, financial insecurity, and related conditions (such as ME/CFS and dysautonomia).
    • The list is hosted on Notion, allowing users to search and filter for specific source needs.
    • This project is ongoing, and we will be adding more sources on an ongoing basis. If you would like to be added or have other feedback, please email LongCovidSourceList@gmail.com!
    https://twitter.com/fi_lowenstein/status/1481399096711606273

    To further explain the motivations for this project and provide some advice on how to use the source list, I did a Q&A with Fiona. Our conversation included the gaps in Long COVID news coverage, connecting the dots between Long COVID and other chronic conditions, recommendations for interviewing Long COVID patients, suggestions for covering this condition in year three of the pandemic, and much more. This interview has been lightly edited and condensed for clarity.

    Betsy Ladyzhets: Why did you want to do this project? Why was it worth putting the time and effort into making this source list?

    Fiona Lowenstein: I think there were two things. One was almost like a personal desire to have fewer media inquiries in my own inbox. I was receiving a lot of emails from journalists who were looking for very specific types of Long COVID sources. Part of that was because I started the support group Body Politic, and people were reaching out, asking me to post stuff in the group. Also, I have written a lot of stories on Long COVID and interviewed a lot of patients, and so people wanted help reaching more patients.

    I knew that a lot of the support group leaders were very burnt out and kind-of exhausted, and that media requests are one of the biggest sources of, like, email stress. And I wanted to think about, is there a way to just ease this process for everyone? I was also noticing that journalists were getting frustrated with how long it was taking to get in touch with [Long COVID] sources, because so many of these groups are run by chronically ill people, and a lot of them are volunteers. They’re not always able to respond to an email in twelve hours.

    Part of [the motivation] was also feeling like the news coverage of Long COVID, a lot of it focuses on the same people and the same stories. I’m someone that has been included in a lot of those articles, and at a certain point in time, I stopped doing press on my own experience, because I was like, this story is already out there. And I’m not sure it’s even reflective of the average experience of Long COVID, just because I had a lot of privilege that helped me get care and rest through my recovery.

    So, I wanted to see more types of patients talked about, more patients who aren’t necessarily young and super healthy and fit before they got sick. Because that was very much the narrative for a long time. And that is sort-of an ableist narrative, to be emphasizing so strongly that so many of us were young and healthy, and we should care about our chronic illnesses because of that.

    Also, I know that Long COVID coverage is going to have to go deeper and is already starting to go deeper in the coming year. Most news outlets have had at least one story explaining what Long COVID is. But we’re now at a point where we’re going to have to delve deeper into, like, what are the financial risks? What toll does [Long COVID] take on relationships? How are people navigating workplace accommodations? What about these specific symptom clusters that might morph over time? What about people who have additional diagnoses [of other chronic conditions] on top of having Long COVID?

    And the last thing was, I want to connect the dots between Long COVID and other post-viral or infection-initiated chronic illnesses, like ME/CFS, dysautonomia, and other diagnoses that people with Long COVID have received. These are also diseases that have a lot in common, both in terms of symptoms and the way that they present but also in terms of social and political issues with regards to getting care, getting funded research, etc.

    I think those of us who have had Long COVID and been involved or even been a fly on the wall in this advocacy work have seen how people with related chronic illnesses are not getting as much media attention. Even though they are really helping the Long COVID advocacy movement in a huge way, and helping patients on a day-to-day basis. So, that was why I wanted to include people with related conditions and experiences [on the source list], ideally, as well.

    BL: Yeah, that makes sense. When we were starting to put together the Google forms [used to collect source’s information] and thinking about who we wanted to send them to, what were some of the things that you were considering?

    FL: I was thinking a lot about the patient side of things. I wanted to connect with the leaders of the big [Long COVID] support groups, especially the private support groups, because the private support groups are a little more insular and more highly moderated. They’re the places where we can assume that a larger majority of the members actually have Long COVID. But the private support groups also have no way for journalists to kind-of see into those ecosystems. So, I wanted to connect with those support group leaders and have them share [the project within their groups]. I also did a lot of sharing on social media, because I’m followed by a lot of Long COVID patients and people living with the illness. And I messaged past sources, other people that I’ve talked to. 

    That being said, I was a little surprised—we got a lot of patient responses, but I think we could have gotten more. (Editor’s note: The list includes over 250 patients and 80 non-patient experts.) I know that there are more [Long COVID] people out there who want to tell their stories. But I think that, among the population of people with Long COVID who want to talk to the press, there are a lot of people who are just burnt out and tired of filling out forms. And there’s also a lot of distrust of the media. There was at least one support group that basically said, “We don’t want to participate in this because we don’t want our members’ information out there for reporters to access, we’ve had so many bad experiences with journalists.”

    That was a tricky thing to navigate. To that end, something I’m hoping to do at some point is organize another media training with some of these support groups, to talk through, like, what are some of the issues that are coming up in the journalist-patient relationship? What are your rights as a source when you’re being interviewed? That sort of thing.

    BL: Was there anything else that surprised you, when you were looking at the form responses? I know one thing that struck me when I was looking at them was, how many patients checked the box for experience with financial instability. I knew that was an issue, but it’s not something that a lot of articles have focused on so far.

    FL: Yeah, that’s a really good point. I filled out the form, because I’ve had Long COVID, and I checked that off, too. I think that, in the Long COVID communities, [financial instability] is such a huge issue, and it’s being talked about constantly. Even for people like myself—I had a relative amount of financial privilege, I had savings that I could rely on after I got sick and couldn’t work. And I had my parents and my partner’s parents, they were able to contribute a little bit to our rent and our groceries and that sort of thing. But it’s still massively set back my finances. So, I think almost everyone has had that experience on some level.

    I think one thing that surprised me was how many people had a diagnosis of another condition on top of Long COVID. It’s good, it’s heartening to see that people are getting diagnosed with things like dysautonomia, myalgic encephalomyelitis, and mast cell activation syndrome. I know that [these diagnoses are] happening a lot with the patient advocates that I know, but those are people who often have the highest levels of access to a clinician or a Long COVID clinic. But [the form responses] made me wonder if maybe also, there’s been so much information-sharing online and between patient groups that people are now able to diagnose themselves with this stuff—which is very common in chronic health communities because it can be so hard to get a diagnosis. 

    So, it was interesting seeing that so many people have checked off dysautonomia and these other things, because it made me feel like, okay, there actually is a pretty large group of people that are very aware of these other illnesses. I could not have told you what dysautonomia was, prior to getting COVID—even though I technically had a form of it, it turns out, before getting COVID. It seems indicative of the extent to which community information sharing has spread, and actually helps people figure out what they’re dealing with.

    And those diagnoses are also really helpful for figuring out your symptom management techniques. Like, I learned rest and pacing from people in the ME community. So that’s a huge part of it, too: it’s having that community that you can look to, in addition to Long COVID. People who have been sicker for longer, and research has been going on for longer, and you can learn from [these other chronic illness patients].

    BL: What recommendations do you have for people who are using the source list?

    FL: There are a couple of kind-of broad stroke recommendations that we tried to account for in some of the questions we included on the list.

    For example, one thing that I have said to colleagues and also publicly throughout the pandemic is: if you are a journalist reporting on Long COVID, you unfortunately have to have a pretty flexible schedule with your interviews, because this is an unpredictable illness. Someone could tell you, “Yeah, I’m available tomorrow at 2pm.” And then they could end up being really sick at that time. So, in the questions for patients, there’s a space where they can indicate how quickly they think, on average, they’ll respond to reporters. Hopefully that will help with this issue of, the urgency of tight deadlines, while trying to report on an issue in which people can’t always get back to you in a short timeframe.

    Just be aware that these are people who, even though a lot of them may not be working, are dealing with a full schedule of managing their own health. It’s also important to know that there is distrust amongst this population, in terms of interacting with journalists and reporters. I’m not saying that exists with every single one COVID patient, and lots of people have had really good experiences talking to journalists.

    But still, for that reason, it’s sometimes helpful, when you’re interviewing someone with Long COVID, to explain why you’re asking the questions you’re asking. For example, on the source list, we’ve included both people who have tested positive for COVID-19—via a PCR test or other diagnostic test—and people who have not tested positive. Some of those people who have not tested positive have a clinical diagnosis of COVID or Long COVID, while others do not. It’s important to understand the difference between those testing statuses and those diagnosis statuses. These statuses may have something to do with how intense the person’s acute symptoms were, but it has more to do with where the person was at the time that they sought the test, what time in the pandemic it was, and what sorts of privilege they might have or not have within the healthcare system in terms of accessing a test. Like, do they have a car and can they drive themselves to get a test? 

    That [testing status] question comes up a lot. And I think that journalists, when asking about just testing status, a helpful thing to do is explain why you’re asking. You could say, “I’m going to include people of all testing statuses in this article, because I understand that not everyone who has Long COVID was able to get a positive test for an acute COVID infection. But just for the purposes of accuracy, I need to ask, are you someone who had a positive COVID test or did you not have a COVID test? Because I need to include those details.” 

    Also, some people on the list have specified different methods of interview that they are comfortable with. But it never hurts to ask and double check [about interview method]. There are people who have really intense screen sensitivity and light sensitivity, and so emailing is going to be more difficult for them. Then, there are other people for whom a Zoom call or phone call is actually going to be more difficult, and they’d prefer texting, or emailing, or audio messages. I know a lot of times there is sort-of a reticence with journalists to use methods other than a Zoom call. But a lot of Long COVID patients have been communicating super effectively using nontraditional means for the entire pandemic. So, have a bit of trust in their ability to do that.

    BL: Are there any other things that you want journalists to know about talking to Long COVID patients?

    FL: There are a lot of things! One other thing to keep in mind is that everybody has a different level of expertise on Long COVID. A lot of times, I’ll seen articles—or I’ve even been in this position—there are people on our list who have identified themselves as experts on Long COVID, or patient advocates, outside of just their lived experience. Those are people who can, yeah, they might be able to speak to their lived experience, but they’re also going to be able to speak to, like, what they’re seeing in their support group or their experience, trying to advocate for policy change.

    And I think it’s a shame when the stories about those advocates focus only on their own health issues. That happens a lot, just because I think journalists have a hard time finding people who are willing to talk about their own health issues. But be aware that there are a lot of people who have really a higher level of expertise than just, “This is what happened to me in my body,” people who have taken a lot of care and a lot of time to read the latest research on Long COVID and are in touch with doctors and scientists and policymakers. I think treating those people as experts on the subject is important.

    On the flip side, not every Long COVID patient is going to be able to speak to those macro issues, and not every Long COVID patient has the same understanding of what’s happening in their body. There are also a ton of people—and these people probably are not on our list, unfortunately—people who have Long COVID and don’t know what it is, or don’t know that it’s called Long COVID. So, knowing that people’s understandings will vary from individual to individual is important as well, I think.

    And don’t be afraid to interview people with related illnesses! Again, dysautonomia is an incredibly common diagnosis, it seems, for people with Long COVID. But I haven’t really seen many articles that are interviewing other people who have lived with dysautonomia for ten years, or scientists who are studying it, or that sort of thing. 

    BL: Yeah. How would you like to see the source get used?

    FL: We had a media inquiry today [via LongCovidSourceList@gmail.com] that excited me because it was about a really hyper-specific local story. I would love to see more of that. Because I think Long COVID is an illness that does radicalize a lot of people, through getting sick and seeing like, “Oh, no one’s there to take care of me, and the government doesn’t care.” And a lot of people who are angry are organizing in their communities, or they’re even advocating on behalf of themselves.

    I think, in the coming decade, we’re going to learn about more and more of these people who have been doing this [organizing] on the local level. Like, I know of many people who have organized really small support groups in their town or in their city. So, I’d love to see more hyperlocal coverage of how Long COVID is impacting individual communities. I’d also love to see more coverage of caregivers and people with loved ones who have Long COVID, and how folks are navigating those relationships. Because I think there are so many lessons we can learn about disability and chronic illness and relationships in general from those stories. 

    And obviously, I’d love to see more diverse sources. Near the beginning of the pandemic, there was a period of time where there were a lot of stories about health disparities. And we were talking a lot more about the impact of COVID on undocumented populations, or Black and Latinx and Indigenous populations in the US, or the people in rural areas or inner city areas.

    We haven’t really seen a lot of that coverage for Long COVID. Part of that is because no one’s tracking it on a nationwide level, like we don’t have the case counts for Long COVID that we have for COVID infections. But there’s still stories to be done [on this issue]. You can go into a community and all you really need is one person, one source that has Long COVID in that community, to understand: How is that community grappling with this condition? Does that person know anybody else who knows what Long COVID is? Is that person educating everyone in their community on what Long COVID is? How did that person find care? Is there a hospital near them? Those are the stories I’d really like to see more. 

    Those stories, with an emphasis on those populations that were hit hardest at the beginning of the pandemic, and are still hard-hit. Like, I saw the other day that in Los Angeles, where I am, homeless populations have some of the highest rates of COVID infections. That would be a really interesting story and a really important story to look at, what does long-term care look like for those populations? 

    BL: You mentioned the fact that Long COVID cases are not tracked the way so many other COVID metrics are—which, as a data journalist, I definitely consider to be one of the biggest data gaps of the pandemic. Are there any other stories that you would want to see in that vein, or any other coverage areas you would like to see around Long COVID?

    FL: Yeah. I think this idea would take kind of the right type of journalist, probably someone with a deep knowledge of chronic illness communities; it would be interesting to delve into what I was talking about before, in terms of these additional diagnoses that [Long COVID patients] have received and/or self-diagnosed themselves with.

    I’m also very curious about how people get diagnosed with Long COVID, because it seems to be happening in a different way with everyone. There are the people like me, where I don’t have a clinical diagnosis of Long COVID—I don’t think I do, maybe my doctor put something on my chart—but like, I just have a COVID PCR test, and then I have records of going for care for these other related problems. And then I have an additional diagnosis of this kind-of dysautonomia-related thing.

    We do now have an ICD code for Long COVID. But I’m not exactly sure that it’s being used in all situations. And like, if someone gets diagnosed with ME/CFS, are they getting diagnosed with both those ICD codes, or does one diagnosis overrule the other one? So, I think there’s a lot of interesting stuff there. You could also delve into how common it is to self-diagnose and what that looks like when you end up going to the doctor at some point later on. This [story] can be done in a variety of ways. People could also write guides on, “How do you get an accurate diagnosis?” And, “What does a diagnosis mean in terms of your insurance coverage, or your eligibility for disability benefits?”

    I think [disability benefits are] another thing that is going to be huge. I get a lot of emails from people with Long COVID who have been denied long-term disability. One person I was speaking to was from a Republican state, and she was saying, like, “I’m from a state where the government shut down all the COVID-related social programs earlier than in other states. Why would I believe the caseworker in my state is going to take my Long COVID disability case seriously?”

    I think that’s an interesting thing, too. COVID was highly politicized. Long COVID isn’t highly political in the exact same way simply because it’s not something that everybody knows about and is talking about. But there’s that question: if we know that COVID infections and COVID care can sometimes differ state to state based on the political leadership and what sort of funding has been put into healthcare systems, how does that look for Long COVID? What does that mean for people applying for disability benefits? Are people in blue states having an easier time getting approved for long-term disability? Does it not matter? That sort of thing.

    BL: Yeah, that’s a good point. Those were all of my questions—is there anything else that you think is important for people to know about this project or about using the list? 

    FL: Well, I’m curious—I know that you were writing about Long COVID and looking for sources, but I’m kind of curious why you wanted to participate in this project and why it felt important to you?

    BL: I think that, as I said a bit ago, I feel like this is a really important data gap. There’s this feedback loop where, we don’t have really solid numbers about Long COVID, and so people don’t know about it, and so that contributes to the lack of numbers, and then it sort-of spirals in that way. And this [project] seemed like a way to combat that situation, at least a little bit. And also, I like making resources for other journalists, it’s part of the reason why [the COVID-19 Data Dispatch] exists, basically. This project felt like an extension of that goal.

    FL: Yeah, that makes a lot of sense. I think there is an enormous desire for those of us who followed Long COVID from the beginning to see it get its due in the media. And I think, now that we’re entering year three, and we’re hearing that Omicron is potentially more mild—it just feels like, when is it going to be the time that we fully turn our attention to this? In terms of gathering the data and, and writing about it.

  • Malnutrition, other gastrointestinal issues are common in Long COVID

    Did you know that diarrhea, nausea, and vomiting are all common COVID-19 symptoms? I knew they were included on the CDC’s list of symptoms, but I didn’t realize how often these symptoms occur—or how nasty they can get—until I reported this story for Gothamist, a news site run by New York City’s public radio station.

    The story focuses on a recent paper from Northwell Health, a hospital system in NYC. Northwell clinicians investigated rates of gastrointestinal symptoms (or, symptoms in the digestive system) among their COVID-19 patients. Out of 17,500 patients, over 3,200 had gastrointestinal symptoms—almost 20% of the group. These symptoms included diarrhea caused by intestinal infection, bleeding in the GI tract, and malnutrition.

    For several hundred patients, the researchers were able to track their GI symptoms for six months after they left the hospital. This led to another concerning discovery: at the six-month mark, more than half of the patients who’d suffered malnutrition in the hospital were still experiencing this symptom. Same thing for the patients who’d suffered chronic weight loss.

    In reporting this story, I also talked to Lauren Nichols—a Long COVID patient and advocate with Body Politic. She’s been facing COVID-related GI symptoms for eighteen months, ranging from intensive diarrhea in spring 2020 to an inability to gain weight and, now, potential autoimmune issues. Many other Long COVID patients have experienced these symptoms, according to a large survey of patients.

    As I wrote a couple of weeks ago, Long COVID provides a great argument in favor of getting vaccinated. This disease isn’t just a run-of-the-mill cough, or flu—it can truly mess up people’s lives in the long term.