The CDC’s new COVID-19 dashboard suggests that the national situation is totally fine, because hospitalizations are low. But is that correct?
On Thursday, the CDC revamped its COVID-19 dashboard in response to changing data availability with the end of the federal public health emergency. (For more details on the data changes, see my post from last week.) The new dashboard downplays continued COVID-19 risk across the U.S.
Overall, the new dashboard makes it clear that case counts are no longer available, since testing labs and state/local heath agencies aren’t sending those results to the CDC anymore. You can’t find case counts or trends on the homepage, at the top of the dashboard, or in a county-level map.
Instead, the CDC is now displaying data that shows some of COVID-19’s severe impacts— hospitalizations and deaths—without making it clear how widely the virus is still spreading. Its key metrics are new hospital admissions, currently-hospitalized patients, emergency room visits, and the percentage of recent deaths attributed to COVID-19. You can find these numbers at national and state levels in a revamped “trends” page, and at county levels in a “maps” page.
The “maps” page with county-level data has essentially replaced the CDC’s prior Community Level and Transmission Level page, where users were previously able to find COVID-19 case rates and test positivity rates by county. In fact, as of May 13, the URL to this maps page is still labeled as “cases” when you click into it from the main dashboard.
While these changes might be logical (given that case numbers are no longer available), I think the CDC’s design choices here are worth highlighting. By prioritizing hospitalizations and deaths, the CDC implicitly tells users of this dashboard that the virus should no longer be a concern for you unless you’re part of a fairly small minority of Americans at high risk of those severe outcomes.
But is that actually true, that COVID-19 is no longer a concern unless you’re going to go to the hospital? I personally wouldn’t agree. I’d prefer not to be out sick for a week or two, if I can avoid it. And I’d definitely like to avoid any long-term symptoms—or the long-term risks of heart problems, lung problems, diabetes, etc. that may come after a coronavirus infection.
These outcomes still persist after a mild COVID-19 case. But the current CDC data presentation makes it hard to see those potential outcomes, or your risk of getting that mild COVID-19 case. The agency still has some data that can help answer these questions (wastewater surveillance, variant surveillance, Long COVID survey results, etc.) but those numbers aren’t prioritized to the same degree as hospitalizations and deaths.
I’m sure the CDC data scientists behind this new dashboard are doing the best they can with the information they have available. Still, in this one journalist’s opinion, they could’ve done more to make it clear how dangerous—and how widely prevalent—COVID-19 still is.
With the end of the Public Health Emergency, the CDC has removed the COVID transmission map from their website.
For other dashboards that continue to provide updates, see my list from a few weeks ago. I also recommend looking at your state and local public health agencies to see what they’re doing in response to the PHE’s end.
We’re now less than one week out from May 11, when the federal public health emergency (or PHE) for COVID-19 will end. While this change doesn’t actually signify that COVID-19 is no longer worth worrying about, it marks a major shift in how U.S. governments will respond to the ongoing pandemic, including how the disease is tracked and what public services are available.
I’ve been writing about this a lot in the last couple of months, cataloging different aspects of the federal emergency’s end. But I thought it might be helpful for readers if I compiled all the key information in one place. This post also includes a few new insights about how COVID-19 surveillance will change after May 11, citing the latest CDC reports.
What will change overall when the PHE ends?
The ending of the PHE will lead to COVID-19 tests, treatments, vaccines, and data becoming less widely available across the U.S. It may also have broader implications for healthcare, with telehealth policies shifting, people getting kicked off of Medicaid, and other changes.
Free COVID-19 vaccines, tests, and treatments will run out after the federal government’s supplies are exhausted. (Health experts project that this will likely happen sometime in fall 2023.) At that point, these services will get more expensive and harder to access as they transition to private healthcare markets.
We will have fewer COVID-19 metrics (and less complete data) to rely on as the CDC and other public health agencies change their surveillance practices. More on this below.
Manyvaccination requirements are being lifted. This applies to federal government mandates as well as many from state/local governments and individual businesses.
The FDA will phase out its Emergency Use Authorizations (EUAs) for COVID-19 products, encouraging manufacturers to apply for full approval. (This doesn’t mean we’ll suddenly stop being able to buy at-home tests—there’s going to be a long transition process.)
Healthcare worker shortages may get worse. During the pandemic emergency, some shifts to work requirements allowed facilities to hire more people, more easily; as these policies are phased out, some places may lose those workers.
Millions of people will lose access to Medicaid. A federal rule tied to the PHE forbade states from kicking people off this public insurance program during the pandemic, leading to record coverage. Now, states are reevaluating who is eligible. (This process actually started in April, before the official PHE end.)
Telehealth options may become less available. As with healthcare hiring, policies during the PHE made it easier for doctors to provide virtual care options, like video-call appointments and remote prescriptions. Some of these COVID-era rules will be rolled back, while others may become permanent.
People with Long COVID will be further left behind, as the PHE’s end leads many people to distance themselves even more from the pandemic—even though long-haulers desperately need support. This will also affect people who are at high risk for COVID-19 and continue to take safety precautions.
Pandemic research and response efforts may be neglected. Lee referenced the “panic and neglect” cycle for public health funding: a pattern in which governments provide resources when a crisis happens, but then fail to follow through during less dire periods. The PHE’s end will likely lead us (further) into the “neglect” part of this cycle.
A lot of the information isn’t new, such as the phasing out of Community Level metrics for counties (which I covered last week). But it’s helpful to have all the details in one place. Here are a few things that stuck out to me:
Hospital admissions will be the CDC’s primary metric for tracking trends in COVID-19 spread rather than cases. While more reliable than case counts, hospitalizations are a lagging metric—it takes typically days (or weeks) after infections go up for the increase to show up at hospitals, since people don’t seek medical care immediately. The CDC will recieve reports from hospitals at a weekly cadence, rather than daily, after May 11, likely increasing this lag and making it harder for health officials to spot new surges.
National case counts will no longer be available as PCR labs will no longer be required to report their data to the CDC. PCR test totals and test positivity rates will also disappear for the same reason, as will the Community Levels that were determined partially by cases. The CDC will also stop reporting real(ish)-time counts of COVID-associated deaths, relying instead on death certificates.
Deaths will be the primary metric for tracking how hard COVID-19 is hitting the U.S. The CDC will get this information from death certificates via the National Vital Statistics System. While deaths are reported with a significant lag (at least two weeks), the agency has made a lot of progress on modernizing this reporting system during the pandemic. (See this December 2021 post for more details.)
The CDC will utilize sentinel networks and electronic health records to gain more information about COVID-19 spread. This includes the National Respiratory and Enteric Virus Surveillance System, a network of about 450 laboratories that submit testing data to the CDC (previously established for other endemic diseases like RSV and norovirus). It also includes the National Syndromic Surveillance Program, a network of 6,300 hospitals that submit patient data to the agency.
Variant surveillancewill continue, using a combination of PCR samples and wastewater data. The CDC’s access to PCR swab samples will be seriously diminished after May 11, so it will have to work with public health labs to develop national estimates from the available samples. Wastewater will help fill in these gaps; a few wastewater testing sites already send the CDC variant data. And the CDC will continue offering tests to international travelers entering the country, for a window into global variant patterns.
The CDC will continue tracking vaccinations, vaccine effectiveness, and vaccine safety. Vaccinations are generally tracked at the state level (every state health agency, and several large cities, have their own immunization data systems), but state agencies have established data sharing agreements with the CDC that are set to continue past May 11. The CDC will keep using its established systems for evaluating how well the vaccines work and tracking potential safety issues as well.
Long COVID notably is not mentioned in the CDC’s reports. The agency hasn’t put much focus on tracking long-term symptoms during the first three years of the pandemic, and it appears this will continue—even though Long COVID is a severe outcome of COVID-19, just like hospitalization or death. A lack of focus on tracking Long COVID will make it easier for the CDC and other institutions to keep minimizing this condition.
On May 11, the CDC plans to relaunch its COVID-19 tracker to incorporate all of these changes. The MMWR on surveillance changes includes a list of major pages that will shift or be discontinued at this time.
Overall, the CDC will start tracking COVID-19 similar to the way it tracks other endemic diseases. Rather than attempting to count every case, it will focus on certain severe outcomes (i.e., hospitalizations and deaths) and extrapolate national patterns from a subset of healthcare facilities with easier-to-manage data practices. The main exception, I think, will be a focus on tracking potential new variants, since the coronavirus is mutating faster and more aggressively than other viruses like the flu.
What should I do to prepare for May 11?
If you’ve read this far, you’re probably concerned about how all these shifts will impact your ability to stay safe from COVID-19. Unfortunately, the CDC, like many other public agencies, is basically leaving Americans to fend for themselves with relatively little information or guidance.
But a lot of information sources (like this publication) are going to continue. Here are a few things I recommend doing this week as the PHE ends:
Look at your state and local public health agencies to see how they’re responding to the federal shift. Some COVID-19 dashboards are getting discontinued, but many are sticking around; your local agency will likely have information that’s more tailored to you than what the CDC can offer.
Stock up on at-home tests and masks. This is your last week to order free at-home/rapid tests from your insurance company if you have private insurance. It’s also a good time to buy tests and masks; many distributors are having sales right now.
Figure out where you might get a PCR test and/or Paxlovid if needed. These services will be harder to access after May 11; if you do some logistical legwork now, you may be more prepared for when you or someone close to you gets sick. The People’s CDC has some information and links about this.
Contact your insurance company to find out how their COVID-19 coverage policies are changing, if you have private insurance. Folks on Medicare and Medicaid: this Kaiser Family Foundation article has more details about changes for you.
Ask people in your community how you can help. This is a confusing and isolating time for many Americans, especially people at higher risk for COVID-19. Reaching out to others and offering some info or resources (maybe even sharing this post!) could potentially go a long way.
That was a lot of information packed into one post. If you have questions about the ending PHE (or if I missed any important details), please email me or leave a comment below—and I’ll try to answer in next week’s issue.
The CDC’s Community Levels suggest (perhaps inaccurately!) that the U.S. has little to worry about from COVID-19 right now. The agency is set to stop calculating these metrics next month.
As we’ve gotten closer to May 11, the official ending of the federal public health emergency for COVID-19, I’ve tried to collect news on how this change will impact COVID-19 data availability. We know, for example, that the CDC will lose some of its authority to collect data from state and local health agencies, and that PCR testing numbers will become even less accurate.
This week, another key change became public: the CDC will stop reporting COVID-19 Community Levels, according to reporting by Brenda Goodman at CNN. The agency is overall planning to shift from using case data to hospitalizations and wastewater surveillance.
The CDC’s Community Levels are county-level metrics based on cases and hospitalizations. In February 2022, the agency switched to these metrics from its prior Transmission Levels (which were based on cases and test positivity), and essentially changed its national COVID-19 map from bright red to pastel green-yellow-orange overnight.
Community Levels have generally made the U.S.’s COVID-19 situation look better than it really is over the last year, since these metrics relied on hospitalizations, a lagging indicator, and were set to high thresholds for recommending safety measures. Even so, the metrics gave Americans an easy way to look at the COVID-19 situation in their county or region.
On May 11, that county-level information will no longer be available, according to Goodman’s reporting. When the public health emergency ends, the CDC will no longer be able to require COVID-19 testing labs to report their results—so this already-spotty information will become even less accurate. While test results at the national level might still be helpful for following general trends, it will be harder to interpret more local data.
“We’re not going to lose complete surveillance, but we will lose that hyperlocal sensitivity to it perhaps,” an anonymous source at the CDC told Goodman. These more local metrics “simply cannot be sustained” due to reporting changes, the source said.
In absence of county-level case data, the CDC plans on utilizing hospitalizations and wastewater surveillance to track COVID-19, according to the CNN report. The agency might focus on tracking COVID-19 at specific healthcare settings in a reporting network, similar to its surveillance for endemic diseases like flu and RSV, rather than trying to count every single severe COVID-19 case.
Hospitalization data tend to lag behind cases, so wastewater surveillance will be important to provide early warnings about potential new coronavirus variants or surges. However, the country’s wastewater surveillance network is still patchy: some states have a sewage testing site in every county, while others only have a handful. Our data will be biased, based on which health departments have invested in this technology.
It’s unsurprising to see the CDC plan this COVID-19 reporting change, given the powers it will lose on May 11. But I’m still disappointed. I’ve followed the U.S.’s incomplete surveillance for endemic diseases, and I hoped that continued COVID-19 tracking would provide an opportunity for improvement. Instead, it looks like we’re going to revert to something like our flu tracking, with wastewater surveillance unevenly tacked on.
The May 11 changes will inevitably have a huge impact on the Americans who are still trying to stay safe from COVID-19, especially those with health conditions that make them more vulnerable to severe symptoms. Without reliable data, people will be unable to identify when spread is high or low in their community. I expect some will simply shrug off the risks (but may regret that choice later), while others will anticipate that COVID-19 is everywhere, all the time, and retreat from public activities.
And from the public health perspective, less data will make it harder to identify concerning new variants or potential surges. For more on these challenges, I recommend this article by KFF Health News reporter Sam Whitehead, published in CNN and other outlets.
“We’re all less safe when there’s not the national amassing of this information in a timely and coherent way,” Anne Schuchat, former principal deputy director of the Centers for Disease Control and Prevention, told Whitehead.
The CDC has archived a couple of major datasets providing COVID-19 cases and deaths by state and county.
The CDC is now updating its COVID-19 cases and deaths data weekly, instead of daily, as I covered last week. This shift goes beyond the agency’s public dashboard: the CDC has also archived datasets with state-and county-level data providing COVID-19 cases and deaths, which were previously updated daily on data.cdc.gov.
These datasets previously included the underlying numbers behind the CDC’s dashboard, allowing data-savvy Americans to produce their own analysis and visualizations. I learned about the archiving via a Twitter thread by Iowa data expert Sara Anne Willette, who uses the CDC’s data to update an independent dashboard tracking COVID-19 in her state.
To replace these daily datasets, the CDC has posted a new dataset, “Weekly COVID-19 County Level of Community Transmission Historical Changes.” It appears to provide COVID-19 cases and test positivity rates by county, by week—but the data aren’t actually available yet. This dataset currently includes zero rows while the CDC resolves a “processing issue.”
None of this is particularly surprising, considering that the CDC is clearly deprioritizing COVID-19 tracking and allocating its data analysis resources elsewhere. But it remains frustrating for those of us who still want to know what’s going on with COVID-19 in our communities.
In April, the CDC launched a new center called the Center for Forecasting and Outbreak Analytics (or CFA). The new center aims to develop models of COVID-19 and other infectious diseases, while also helping public health agencies and individual Americans act on the information. One of CFA’s lead scientists compared it to the National Weather Service.
COVID-19 case data are becoming increasingly unreliable as PCR testing is less accessible and more people use at-home tests;
Hospitalization data are more reliable, but lag behind actual infections and may soon be unavailable in their current, comprehensive format;
Wastewater surveillance and other promising sources are not yet ready to replace clinical datasets;
A slow hiring process, as the center aims to bring on 100 scientists and communicators;
The CDC’s limited authority over state and local health agencies, and over the public.
At the COVID-19 Data Dispatch today, I’m sharing one of the interviews I did for the FiveThirtyEight story. I talked to Jason Salemi, an epidemiologist at the University of South Florida College of Public Health, whom you may know from his excellent dashboard and Twitter threads providing detailed COVID-19 updates.
While Salemi isn’t focused specifically on forecasting, he has a lot of insight about interpreting COVID-19 data and using the data for public health decisions. And I think he shares my frustration about the lack of safety measures that are being implemented across the U.S. at this dangerous point in the pandemic.
For context, this interview took place about one month ago, while BA.2/BA.2.12.1 were driving a surge in the Northeast but hadn’t quite hit other parts of the country yet. This interview has been lightly edited and condensed for clarity.
Betsy Ladyzhets: I wanted to start by asking, what do you see as the current state of trying to keep track of COVID in the United States? Like, what are some of the metrics that you’re looking at right now? What are some challenges that you’re facing as we deal with case numbers becoming less reliable?
Jason Salemi: Definitely the case numbers issue. Throughout the entire pandemic, we all know that the case numbers that we learn about when somebody actually tests positive and that information gets recorded somewhere, reported to a State Department of Health and ultimately to the CDC, that’s always underestimated the true number of infections that’s been circulating in the population. Obviously, very early in the pandemic, that was really, really bad—we were mostly picking up people as they were getting sick and landing in the hospital. But as testing expanded, obviously, we did a much better job of being able to gauge what was happening with true infections by relying on the reported case numbers.
However, during Omicron, and especially with the increased use of at-home testing—a lot of those at-home tests, if the person tested positive, were not making their way into a system that would actually get translated into the officially reported numbers. And negative at-home test results—those are definitely not making their way to public health agencies. I think in some jurisdictions, you were finding that 30%, 40% of all testing was actually antigen testing, and a significant portion of those were the at-home antigen test.
More recently, I think the official numbers that we hear about on a daily basis in terms of official COVID-19 cases, is becoming an increased undercount of the true number of infections that are circulating. Which is pretty striking, considering how much we’ve seen the numbers go up in the past few weeks. So, relying on officially reported cases does mean a lot less. But I still do believe that if you’re looking at—not necessarily where the numbers are exactly, but the trends in the numbers, how those numbers are changing over time—you can at least get a good feel for whether or not things are getting better or worse, even by using the COVID-19 case numbers.
Now, when you supplement that with things like wastewater numbers, data that are not biased by people taking advantage of testing or how they test, the wastewater numbers are maybe a better gauge for truer trends in the amount of viral spread. But again, even with wastewater numbers, two big things about those: number one is, it’s certainly not available, at least not that I can tell, for a lot of jurisdictions throughout the United States… It’s not available consistently across the country.
And number two, there’s nothing in those wastewater numbers where you actually can gauge: okay, this is the actual level of infection. What it helps us to do is, it’s a leading-edge indicator, where early on, we can say, “Oh, wow, we see an increase, a pretty pronounced increase in a particular area over time.” And hopefully, if we were doing things proactively, we could use those data to then implement some sort of concerted mitigation. So, this issue has become more of a challenge. But in many communities, we still can rely on how case numbers are changing over time to loosely gauge transmission rates.
Then, of course, a lot of people say, “It’s all about the hospitalization data, let’s utilize that.” Although I’d always love more metrics included in that [hospitalization] data set, it is something that, for some time now, we actually have consistently measured, at the national level, for every single state. You can get down to the hospital level, in some cases, and even by age group. We can have a decent understanding of how many people are being hospitalized with COVID 19. The nice thing about that is the consistency, and the fact that this [hospitalization dataset] is available everywhere, and we therefore have a decent resource that is capable of picking up indicators of more severe illness.
But there are a lot of problems with the hospitalization data: namely, it’s a lagging indicator. Ultimately, if we were to rely exclusively on COVID-19 hospitalization rates and hospital capacity issues—those indicators lag new infections, often by five to seven days, at least. So, by the time we see those particular metrics rise, we will have lost valuable time to prevent morbidity and mortality. That’s the big [problem].
The other thing is, there’s a lot of legitimacy to when people say, “Well, if a person went to the hospital for a non-COVID-19 related issue, and they just happened to test positive, they may not have been hospitalized because of COVID-19.” I think most are using the term “incidental.” Again, the numbers are not perfect. And when community transmission is as pronounced as it has been during many phases of Omicron, I think we do have a lot of situations where a lot of people are not being hospitalized because of COVID-19. But they are testing positive.
For example, Jackson Health System in Florida was Tweeting out every day during the Omicron phase. And they would say—giving hypothetical numbers here—“We’ve got 250 people who are hospitalized, and that are positive for COVID-19. Of those 250 people, 51% were hospitalized for non-COVID-related reasons.” Some areas would give you more specifics, they would also break down by vaccinated versus unvaccinated. You get a lot of more rich, detailed data from some areas, but obviously, that’s not consistent across the country. In fact, I think it’s pretty rare.
BL: Yeah, that point about hospitalizations being a lagging indicator is definitely something I want to highlight the story. And it seems very complicated, because I have heard from a couple of the modeling experts I’ve talked to that if you look at something like hospital admissions, specifically, that is less lagging. But still, overall, if you think about, like you were saying, trying to prevent more people from getting sick—even by the time you just see more hospital admissions, that’s still bad. You’ve still lost your chance to put in new mask measures, or whatever the case may be.
JS: Oh, absolutely. And, you know, if we really were in a state right now, where getting infected really did no damage to people, it never caused any severe illness, we would obviously care less about transmission levels. Although you could always use the argument that the more we let COVID-19 circulate, the more likely it is that new variants will emerge with potentially more dangerous characteristics. So, even if it wasn’t causing a lot of severe illness, you’ve always got that aspect of it.
But we are certainly not yet at a stage in which we can say [getting infected does no damage]—even though for the average individual Omicron is less severe when we compare it to something like Delta. But we paid a steep price in many areas in the United States to get the infection-acquired immunity and vaccine-acquired immunity that seems to be blunting the effects of Omicron. Right now, that’s why we’re not seeing the rise in hospitalization rates as steep as the rise in case rates.
But we are still seeing people getting hospitalized, an increasing number of people over the past couple of months. We’re not yet in a position where COVID-19 is not causing any damage. And we’re largely ignoring things like Long COVID. Just because somebody doesn’t get hospitalized, that doesn’t mean that [the virus is] still not causing a decrease in the quality of life for many people, and a decreased quality of life that can linger for some time.
BL: Yeah, definitely. And then, another issue with hospitalization data that I wanted to ask you about, because I know you’ve looked at this, is the fact that if you’re using these county risk levels, or community levels, whatever the CDC is calling them—not every county has a hospital. So really, this is data at a somewhat larger regional level. I’m wondering if you could explain why this is an important distinction.
JS: Yeah. And you know, this is not at all a criticism, this is kind-of the nature of the beast, so to speak. There are a lot of communities where—I’ll use Florida, because I’m most familiar with Florida, as an example. We have got a major health care system in Alachua County, which is really not a big county in Florida, not even in the top 20 largest counties. But it is a major area where a lot of people from surrounding smaller counties, like a nine- or ten-county catchment area, if they were to get really sick, that’s where they’re most likely going for treatment. And so, if you have a metric that is based on hospitalization rates, and you don’t have a hospital, obviously, you can no longer really provide a county-level indicator. It has to be more regional. And so you see a lot of variation in how the CDC has to now go from the county level to what they call health services areas.
These [health service areas] are established groupings. In these regions, the overwhelming majority of people in these locations are going to a hospital in the broader health service area. And so it’s confusing, I think, to people: with this newer CDC metric, they wonder, “How is it that there’s no hospital in my county or the county next to me, yet you’re giving me a county-level risk measure that is supposed to be based primarily on hospitalization data?”
And again, I think, some of the nuances of the metric get lost on people… Hospitalization data comes from a broader region [than cases], and there’s a lot of variation. There are some counties that are standalone, like Manatee County in Florida, so there is no health service area, it’s just one county for all measures. But there are some others where more than 15 counties that feed into that health service area. So again, for some people in some communities, I can understand where it’s just confusing and frustrating as to, “What does this risk level really mean, for me and the people that live near me, since the catchment region is so much larger?” This is not a right or a wrong, I understand why CDC does it the way that they do it if they’re trying to get a hospitalization-based measure. But it’s just challenging for people to digest.
BL: Yeah, it’s challenging on that communications front. With the previous transmission levels, you could just kind-of look at the case rate and the positivity rate and be like, “Okay, I get where this is coming from.” But yeah, now it’s a little trickier. Another thing on this topic: I saw a report from POLITICO this morning that is suggesting, basically, if the National Public Health Emergency gets ended this summer, then the CDC might lose its ability to require states or hospitals to actually report the hospitalization data that is basically our best source right now. So, what would the implications be if that happens in a few months?
JS: I’d say pretty significant implications. Look, I’ve tried to give credit where credit is due, like the gains made with improving the federal hospitalization data. I’ve also been a critic when I feel as though we are missing key data sources or data elements. An example is the hospitalization data not having race and ethnicity information, I feel like that’s a big component that would be meaningful.
But even with its limitations, the hospitalization data have been a very, very, very important tool for us to be able to report what’s happening in communities. And obviously, nobody wants to fly blind as it pertains to the pandemic. So if we don’t have uniform reporting from all of these states and jurisdictions, then we have to rely on the willingness of leaders at each state or community level to make similar information available, and to report that information in a timely and consistent manner.
Right now, we are fortunate that we continue to get the hospitalization data updated on a daily basis. And so yeah, that would obviously be a big loss if it were—it’s one thing to not have it required. But if states chose not to report that information, which certainly some states would choose not to… it would be a big loss, depending on what states choose to do to keep the population informed.
Because, to be honest, when we get this national data, it’s a gut reaction that we want to compare states on everything—on death rates, on case rates, on hospitalization rates. To me, this can be a huge mistake. One of the obvious reasons that everybody talks about is age differences, right? Some states have a much higher percentage of older people. But it’s not just age that makes state comparisons difficult. It’s weather, and racial and ethnic distribution, and the job industries in which people can work, population density. So, I don’t really care too much about national-level data being used primarily to make state comparisons and inferences that can be misguided.
But to have consistently reported information across the country, again, is important for us to be able to make more responsible decisions even at the local level. I would hope if that happens [losing the national dataset], we would still have states and cities and counties and communities and all these different geospatial areas continuing to report, collect, and make available to the public meaningful information in a timely manner so we can make responsible decisions.
BL: Yeah, that makes sense. And I know that question of authority and like, what can and can’t you require the states to do, is a large issue for the CDC. I was able to talk to Mark Lipsitch yesterday, he’s one of the scientists who’s working on this new forecasting center. And one challenge he mentioned to me is that the CDC really doesn’t have the authority that it would like to in terms of requiring data reporting. They can’t require every state to start doing wastewater surveillance, they can’t require every state to report vaccine effectiveness data or breakthrough cases. And to me, that just seems like a massive hurdle that they face in trying to do this kind of long-term improvement of infectious disease forecasting.
JS: Yeah—and it’s not just the ability, it’s also having the will. I’ve collaborated with some truly amazing scientists from the CDC for a very long time on a myriad of different initiatives, and I have little doubt that they will compile a team of experts that can analyze meaningful metrics to generate what I imagine will be a wealth of data on where we’re going in the pandemic. But it’s not just about analytic proficiency. I did read on their [CFA’s] site that their stated goal is to enable timely, effective decision-making to improve outbreak response. But how are we going to utilize those data to make recommendations? What outcomes are they going to emphasize? What communities are we thinking about when we make those recommendations?
A lot of people talk about the measures we use, and which ones are best, and how we collect the data, and the validity, and the sophistication of the approaches that we use to either nowcast or forecast into the future. But to me, it’s also the way in which we operationalize those measures for public health recommendations. That’s where a lot of the talk is now about the measures being utilized by CDC. So whether it’s their four-level community transmission measure, or that newer three-level measure that’s based mainly on hospitalization data—how we’re using that to make recommendations, it says something about what the agencies who establish those boundaries are willing to accept.
For example, I was just looking at some data again, when I did that thread this morning. The highest level on the community transmission metric, that used to indicate 100 cases or more per 100,000 people over the most recent seven-day window. Right now, based on the data that I just ran, we’ve got 105 counties in the United States with a population of at least 250,000—not just small counties, but large ones—that have a low community level [the CDC’s more recent metrics], the lowest possible, but they have a transmission level that is higher than that 100 per 100,000 threshold.
And more importantly, we’ve got 28 counties—again, with a population of 250,000 or more—that are classified as medium level. That is a level with no recommendations for mask-wearing in public indoor settings. And those 28 counties have a case rate that is more than triple the threshold for high transmission, that’s 300 per 100,000, over the past seven days. You expect that medium level to change to high in the not-to-distant future for many of these areas.
So again, it’s one thing to collect the metrics and have skilled analysis. But what we do with those measures and that analysis, is just as meaningful. And what does it mean, if we have an area that has really pronounced transmission—and we know in the past, that pronounced transmission means that the virus is going to be exceedingly good at finding vulnerable populations—and we’re not having any meaningful population-based recommendations…
When I looked, some of these counties were at like 400 per 100,000 [cases in a week], four times the threshold for the high transmission level [under the old CDC guidance], and they’re still not at a level where we’re supporting or recommending mask-wearing in public indoor settings. That’s pretty shocking. And I think that’s why anecdotally, now, even in my area, I’m just hearing about more and more people daily, that are not able to come to work. A lot of people are getting infected. And you’re seeing that in the rising numbers.
BL: Absolutely. I mean, isn’t the threshold for moving from low to medium under the new community levels 200 new cases per 100,000 [per week, regardless of hospitalization numbers]?
JS: Yeah, right. So even if you had no rise in hospitalizations, you can have a progression to the medium level. But that is now twice what the highest transmission threshold used to be. And again, I’m looking at counties that are in that medium level that now have almost twice even that newer threshold.
We’re not yet in a situation where COVID is not causing any severe illness whatsoever. We’re ignoring a lot of the ramifications of Long COVID, we’re ignoring the fact that, when community spread has gotten so pronounced, you tend to have the virus easily, efficiently finding the most vulnerable people in those communities and still inflicting damage.
I just feel like we’re missing an opportunity. We’re not talking about shutdowns, we’re talking about simple measures that we can put in place and recommend to people to try and balance having, normal living with putting reasonable but important precautions in place. Because that ultimately will prevent a lot of morbidity and mortality. And I feel like that’s maybe the big missed opportunity right now.
So, I’d be excited to see a new forecasting center come out of the CDC. They are very adept scientists. But it’s ultimately, what do we do? What do we do with the data that emerges out of that center? And what recommendations, simple recommendations, do we end up giving to the public based on those analyses?
BL: I totally agree. One of the new center’s focuses is that they want to hire a bunch of science communicators to think about these things. But still, I guess I’m a little skeptical about how much they’re gonna really be able to have an impact here, when we’re already at such a polarized position in the pandemic.
JS: Yeah, it’s not that any of this is easy. No matter what you do, you’re going to upset a whole lot of people nowadays. I speak strictly from a scientist’s perspective. And I really do get all sides of this equation, like the businesses and the very real toll that the pandemic has taken on people. And so it is, no matter what you do, there is a balance that you have to achieve.
But when I start to see—again, I’m going more from what has transpired specifically in Florida. And a lot of the talk this time last year, after we had the availability of vaccines, things were looking great for Florida. Numbers were really low. And that was pretty much throughout the United States, we had the vaccines, though we still heard a lot about protecting the most vulnerable, the oldest in our communities. And even as the cases started to rise, during Delta, it was like, well, just protect the vulnerable.
But again, when community transmission gets that pronounced, the virus will continue to find the most vulnerable. And it ended up inflicting by far the largest death toll in Florida than we’ve had at any point in the pandemic, after vaccines were available for a long period of time. And that included a significant percentage of people who were not seniors. So, it’s tough, but still, people’s livelihood and lives are on the line when we’re talking about COVID.
(Useless) Community Levels on the left; (useful) Community Transmission Levels on the right. Charts via the CDC.
Anyone who’s been regularly reading the COVID-19 Data Dispatch for the last few weeks can probably tell that I think the CDC’s Community Levels are pretty useless. I was critical of these new metrics when the agency changed its guidance from the old Community Transmission Levels back in February. And during the BA.2 surge, I’ve pointed out how the CDC’s Community Levels map makes it look like the U.S. is doing fine at managing COVID-19 when, in fact, we are doing anything but.
If you need a refresher, here are a few of the problems with the Community Levels:
The guidance overly uses hospitalization metrics; while these metrics (especially hospital admissions) are very reliable in showing COVID-19’s impact on the healthcare system, they lag behind actual infections and completely ignore Long COVID.
Hospitalizations are actually a regional metric, not a county-level metric (since plenty of U.S. counties do not have hospitals). As a result, the CDC’s Community Levels calculations are confusing and difficult to replicate in some places.
Thresholds in the Community Levels system, already using lagging indicators, are set very high—to the point that, by the time a county reaches the high level, its healthcare system is already in big trouble.
The CDC does not recommend universal masking until a county reaches the high level; it only recommends one-way masking for vulnerable people, which we know doesn’t really work, at lower levels.
Essentially, these Community Levels are so lenient that many state and local leaders have taken the guidance as an excuse to avoid instituting new COVID-19 safety measures during the BA.2 surge. In Philadelphia, business owners even cited the CDC’s lenient guidance when suing the city for instituting a new indoor mask mandate.
Moreover, as revealed by a recent article in the Tampa Bay Times, it appears that the CDC is not even consistent with its calculations of these Community Levels. The agency labeled three Florida counties as at medium COVID-19 risk, even though they met all the criteria for high risk, due to a data reporting issue from the Florida state health department.
To quote from the article: “A public health tool isn’t useful if it can be undone by a single data issue, said University of South Florida virologist Michael Teng.”
Reminder, you can still see the CDC’s old Community Transmission Level guidance (which is somewhat more useful for determining one’s actual COVID-19 risk) on the agency’s COVID-19 data portal. Just click the dropdown menu on the county view tab and select Community Transmission Levels.
COVID-19 Data Dispatch 