COVID-19 Data Dispatch

Category: State data

  • How are states reporting COVID-19 in schools?

    How are states reporting COVID-19 in schools?

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    Longtime readers might remember that, back in August, I surveyed the available data on how COVID-19 is impacting American schools.

    At the time, very few states were reporting school-specific data, even as school systems around the nation began to reopen for in-person instruction. In that early survey, I highlighted only Iowa as a state including district-level test positivity data on its COVID-19 dashboard. This dearth of data disappointed, but did not surprise me. There was no federal mandate for states, counties, or school districts to report such data, nor did the federal government compile such information.

    There is still no federal mandate for school COVID-19 data, despite pleas from politicians and educators alike. So, as school systems across the country close out their fall semesters amidst a growing outbreak and prepare for the spring, I decided to revisit my survey. I sought out to find how many schools are reporting on COVID-19 cases in their K-12 schools, which metrics they are reporting, and how often. To get started with this search, I used the COVID Monitor, a volunteer effort run by Rebekah Jones which is compiling K-12 case counts from government sources and news reports.

    Overall, many more states are providing school data now than in August. But the data are spotty and inconsistent; most states simply report case counts, making it difficult to contextualize school infections. (For more on why demoninators are important in analyzing school data, see my October 4 issue.)

    You can see the full results of my survey in this spreadsheet (embedded below). But here are a few key findings:

    • In total, 35 states report case counts in all public K-12 schools. 6 states report in an incomplete form, either not including all schools or not including specific case counts.
    • 9 states do not report school COVID-19 data at all. These states are: Alaska, California, Georgia, Nebraska, Nevada, New Mexico, Oklahoma, Pennsylvania, and Wyoming.
    • Most states update their school data either weekly or biweekly. Only 7 states update daily.
    • Most states do not report counts of deaths and hospitalizations which are connected to school COVID-19 outbreaks. Only 5 states report deaths (Colorado, Kansas, North Carolina, Kentucky, and Virginia), and only 1 state reports hospitalizations (Kansas).
    • Only 3 states report in-person enrollment numbers: New York, Massachusetts, and Texas.
    • New York is the only state to report counts of COVID-19 tests conducted for K-12 students and staff.

    And here are a couple of example states I’d like to highlight:

    • New York has the most complete school data by far, scoring 19 out of a possible 21 points on my index. Not only does the state report enrollment and total tests administered to students and staff, New York’s COVID-19 Report Card dashboard includes the test type (usually PCR) and lab each school is using. Test turnaround times are also reported for some schools. This dashboard should be a model for other states.
    • Indiana has a dashboard that I like because it is easy to find and navigate. You don’t have to search through PDFs or go to a separate dashboard—simply click on the “Schools” tab at the top of the state’s main COVID-19 data page, and you will see cumulative case counts and a distribution map. Clicking an individual school on the map will cause the dashboard to automatically filter. Indiana also reports race and ethnicity breakdowns for school cases, which I haven’t seen from any other state.
    • Texas provides detailed spreadsheets with case counts and on-campus enrollments for over 10,000 individual schools. The state reports new cases (in the past week), total cases, and the source of school-related infections (on campus, off campus, and unknown). The infection source data suggests that Texas is prioritizing schools in its contact tracing efforts.
    • Minnesota is one state which provides incomplete data. The state reports a list of school buildings which have seen 5 or more COVID-19 cases in students or staff during the past 28 days. Specific case counts are not provided, nor are specific dates on when these cases occurred. If I were a Minnesota parent at one of these listed schools, I’m not sure what I’d be able to do with this information beyond demand that my child stay home.

    As cases surge across the country, more children become infected, and school opening once again becomes a heated debate from New York City to North Dakota, it is vital that we know how much COVID-19 is actually spreading through classrooms. How can we decide if school opening is a risk to students, teachers, and staff if we don’t know how many students, teachers, and staff have actually gotten sick?

    Moreover, how can we understand the severity of this threat without enrollment or testing numbers? Reporting that a single school has seen three cases is like reporting that a single town has seen three cases; the number is worth very little if it cannot be compared to a broader population.

    Volunteer sources such as the COVID Monitor and Emily Oster’s COVID-19 School Response Dashboard are able to compile some information, but such work cannot compare to the systemic data collection efforts that national and state governments may undertake. If you live in one of those nine states that doesn’t report any school COVID-19 data, I suggest you get on the phone to your governor and ask why.

    Also, speaking of New York City, here’s an update to the 3% threshold I reported on last week:

    more higher education content

    Here are the full results of my survey.

    To use this for your own analysis, make a copy of the public Google sheet.

    Support the COVID Data Dispatch

  • Federal data updates, Nov. 22

    America’s federal public health agencies are busy in the lead-up to Thanksgiving, as are the researchers and volunteer networks filling those agencies’ information gaps. Here are three major updates:

    • CDC’s COVID Data Tracker now reports more county-level data: Since it was first published in the spring, the CDC’s COVID-19 data dashboard has included cases and deaths by U.S. county, relying upon data compiled by USA Facts and verified by the agency. As of yesterday, the county dashboard now also reports total PCR tests and test positivity. Testing data have previously been available directly from the HHS (state-level) and the Center for Medicare & Medicaid Services (county-level), but the CDC dashboard is far more accessible. Users can select a specific county and see a variety of trends in cases, tests, and deaths. The data from this dashboard aren’t yet available for download; I’ll report back if this changes.
    • Pharmacies will be able to distribute COVID-19 vaccines: Last week, the HHS announced that the agency has set up partnerships with both national pharmacy chains and networks representing smaller pharmacies in order to broadly distribute COVID-19 vaccines as they become available. (Pfizer applied for Emergency Use Authorization this past Friday.) According to the HHS, these partnerships cover “approximately 60 percent of pharmacies throughout the 50 states, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands.” The press release does not mention how these pharmacies will be plugged into their respective state vaccine registries.
    • How state COVID-19 dashboards are faring: Although many states are reporting more COVID-19 data than they were last spring, their dashboards are overall still not conveying some key metrics, according to a new report from Resolve to Save Lives. This research group, a nongovernmental initiative run by the global health organization Vital Strategies, first reviewed state dashboards in July. (See my first issue for more details.) The new report—along with an interactive map—reflects improvements that states have made since the summer while highlighting what crucial public health information is still missing. Case investigation and contact tracing are two key areas where “data… remained largely unavailable.”
    more federal data

  • HHS changes may drive hospitalization reporting challenges

    This past week, the Department of Health and Human Services (HHS) opened up a new area of data reporting for hospitals around the country. In addition to their numbers of COVID-19 patients and supply needs, hospitals are now asked to report their numbers of influenza patients, including flu patients in the ICU and those diagnosed with both flu and COVID-19.

    The new reporting fields were announced in an HHS directive on October 6. They became “available for optional reporting” this past Monday, October 19; but HHS intends to make the flu data fields mandatory in the coming weeks. The move makes sense, broadly speaking—as public health experts worry about double flu and COVID-19 outbreaks putting incredible pressure on hospital systems, collecting data on both diseases at once can help the federal public health agencies quickly identify and get aid to the hospitals which are struggling.

    However, it seems likely that the new fields have caused both blips in HHS data and challenges for the state public health departments which rely upon HHS for their own hospitalization figures. As the COVID Tracking Project (and this newsletter) reported over the summer, any new reporting requirement is likely to strain hospitals which are understaffed or underprepared with their in-house data systems. Such challenges at the hospital level can cause delays and inaccuracies in the data reported at both state and federal levels.

    This week, the COVID Tracking Project’s weekly update called attention to gaps in COVID-19 hospitalization data reported by states. Missouri’s public health department specifically linked their hospitalization underreporting to “data changes from the US Department of Health and Human Services.” Five other states—Kansas, Wisconsin, Georgia, Alabama, and Florida—also reported significant decreases or partial updates to their hospitalization figures. These states didn’t specify reasons for their hospitalization data issues, but based on what I saw over the summer, I believe it is a reasonable hypothesis to connect them with HHS’s changing requirements.

    Jim Salter of the Associated Press built on the COVID Tracking Project’s observations by interviewing state public health department officials. He reported that, in Missouri, some hospitals lost access to HHS’s TeleTracking data portal:

    Missouri Hospital Association Senior Vice President Mary Becker said HHS recently implemented changes; some measures were removed from the portal, others were added or renamed. Some reporting hospitals were able to report using the new measures, but others were not, and as a result, the system crashed, she said.

    “This change is impacting hospitals across the country,” Becker said in an email. “Some states collect the data directly and may not yet be introducing the new measures to their processes. Missouri hospitals use TeleTracking and did not have control over the introduction of the changes to the template.”

    As the nation sets COVID-19 records and cases spike in the Midwest, the last thing that public health officials should be worrying about right now is inaccurate hospitalization data. And yet, here we are.

    more hospitalization data
  • It is, once again, time to talk about antigen testing

    It is, once again, time to talk about antigen testing

    Long-term readers might remember that I devoted an issue to antigen testing back in August. Antigen tests are rapid, diagnostic COVID-19 tests that can be used much more quickly and cheaply than their polymerase chain reaction (PCR) counterparts. They don’t require samples to be sent out to laboratories, and some of these tests don’t even require specialized equipment; Abbott’s antigen test only takes a swab, a testing card, and a reagent, and results are available in 15 minutes.

    But these tests have lower sensitivity than PCR tests, meaning that they may miss identifying people who are actually infected with COVID-19 (what epidemiologists call false negatives). They’re also less accurate for asymptomatic patients. In order to carefully examine the potential applications of antigen testing, we need both clear public messaging on how the tests should be used, and accessible public data on how the tests are being used already. Right now, I’m not seeing much of either.

    When I first covered antigen testing in this newsletter, only three states were publishing antigen test data. Now, we’re up past ten states with clear antigen test totals, with more states reporting antigen positives or otherwise talking about these tests in their press releases and documentation. Pennsylvania, for example, announced that the governor’s office began distributing 250,000 antigen test kits on October 14.

    Meanwhile, antigen tests have become a major part of the national testing strategy. Six tests have received Emergency Use Authorization from the FDA. After Abbott’s antigen test was given this okay-to-distribute in late August, the White House quickly purchased 150 million tests and made plans to distribute them across the country. Context: the U.S. has done about 131 million total tests since the pandemic began, according to the COVID Tracking Project’s most recent count.

    Clearly, antigen testing is here—and beginning to scale up. But most states are ill-prepared to report the antigen tests going on in their jurisdictions, and federal public health agencies are barely reporting them at all.

    I’ve been closely investigating antigen test reporting for the past few weeks, along with my fellow COVID Tracking Project volunteers Quang Nguyen, Kara Schechtman, and others on the Data Quality team. Our analysis was published this past Monday. I highly recommend you give it a read—or, if you are a local reporter, I highly recommend that you use it to investigate antigen test reporting in your state.

    But if you just want a summary, you can check out this Twitter thread:

    And I’ve explained the two main takeaways below.

    First: state antigen test reporting is even less standardized than PCR test reporting. While twelve states and territories do report antigen test totals, nine are combining their antigen test counts with PCR test counts, which makes it difficult to analyze the use of either test type or accurately calculate test positivity rates. The reporting practices in sixteen other states are unclear. And even among those states with antigen test totals, many relegate their totals to obscure parts of their dashboards, fail to publish time series, report misleading test positivity rates, and engage in other practices which make the data difficult for the average dashboard user to interpret.

    Second: antigen tests reported by states likely represent significant undercounts. Data reporting inconsistences between the county and state levels in Texas, as well as a lack of test reporting from nursing homes, suggest that antigen tests confuse data pipelines. While on-site test processing is great for patients, it cuts out a lab provider which is set up to report all COVID-19 tests to a local health department. Antigen tests may thus be conducted quickly, then not reported. The most damning evidence for underreporting comes from data reported by test maker Quidel. Here’s how the post explains this:

    Data shared with Carnegie Mellon University by test maker Quidel revealed that between May 26 and October 9, 2020, more than 3 million of the company’s antigen tests were used in the United States. During that same period, US states reported less than half a million antigen tests in total. In Texas alone, Quidel reported 932,000 of its tests had been used, but the state reported only 143,000 antigen tests during that same period.

    Given that Quidel’s antigen test is one of six in use, the true number of antigen tests performed in the United States between late May and the end of September was likely much, much higher, meaning that only a small fraction are being reported by states.

    Again: this is for one of six tests in use. America’s current public health data network can’t even account for three million antigen tests—how will it account for 150 million?

    And, for some bonus reading, here’s context from the Associated Press about the antigen test reporting pipeline issue.

    more testing data
  • New, shareable graphics from the COVID Racial Data Tracker

    New, shareable graphics from the COVID Racial Data Tracker

    Twice a week, the COVID Tracking Project’s COVID Racial Data Tracker compiles and standardizes demographic data from every U.S. state and territory. I am intimately familiar with this work because I’m one of those volunteers. I watch the numbers tick up and, inevitably, paint a clear picture of how centuries of racism have left people of color more vulnerable to this pandemic.

    This week, the COVID Tracking Project’s web design team launched a new feature that makes our demographic data more accessible to readers. It’s called Infection and Mortality by Race and Ethnicity: simply click on a state or territory, and the feature will return a chart that compares COVID-19 cases and deaths to that region’s population.

    Here’s the chart for the U.S. as a whole:

    Adjusting case and death values by population makes it much easier to see disparity. For example, while Native Hawaiians and Pacific Islanders are a relatively small fraction of America’s population, they are much more likely to contract the novel coronavirus. Meanwhile, Black, Hispanic/Latino, and indigenous Americans are more likely to die of the disease.

    These charts are easy to share on Facebook, Twitter, and Instagram, and the graphics will be updated automatically when our data updates twice a week. Volunteers who work on this part of the Project are hoping that these charts can make it easier for people to draw attention to COVID-19 disparity in their communities, as well as to the data that are still missing in many states. For example, here’s me yelling about New York.

    Check out the chart for your state, and if you feel compelled, share it. We need people talking about these data in order to drive change. (Also: shout-out to product lead Neesha Wadhwa and other design folks working behind the scenes at the COVID Tracking Project who made these charts possible!)

  • School data update, Sept. 20

    • The CDC was busy last week. In addition to their vaccination playbook, the agency released indicators for COVID-19 in schools intended to help school administrators make decisions about the safety of in-person learning. The indicators provide a five-tier system, from “lowest risk of transmission” (under 5 cases per 100,000 people, under 3% test positivity) to “highest risk” (over 200 cases per 100,000 people, over 10% test positivity). It is unclear what utility these guidelines will have for the many school districts that have already started their fall semesters, but, uh, maybe New York City can use them?
    • Speaking of New York: the state’s dashboard on COVID-19 in schools that I described in last week’s issue is now live. Users can search for a specific school district, then view case and test numbers for that district’s students and staff. At least, they should be able to; many districts, including New York City, are not yet reporting data. (The NYC district page reports zeros for all values as of my sending this issue.)
    • Los Angeles Unified, the nation’s second-largest school district, is building its own dashboard, the Los Angeles Times reported last week. The district plans to open for in-person instruction in November or later, at which point all students and staff will be tested for COVID-19. Test results down to the classroom level will be available on a public dashboard.
    • Wisconsin journalists have stepped in to monitor COVID-19 outbreaks in schools, as the state has so far failed to report these data. A public dashboard available via the Milwaukee Journal Sentinel and the USA Today Network allows users to see case counts and resulting quarantine and cleaning actions at K-12 schools across the state. Wisconsin residents can submit additional cases through a Google form.
    • According to the COVID Monitor, states that report K-12 COVID-19 case counts now include: Arkansas, Hawaii, Kentucky, Louisiana, Mississippi, New Hampshire, Ohio, South Carolina, South Dakota, Tennessee, Texas, and Utah. Some of these state reports are far more precise than others; Texas and Utah, for example, both report only total case counts. The COVID Monitor reports over 10,000 COVID-19 confirmed cases in K-12 schools as of September 20, with another 17,000 reported cases pending.
    • A recent article in the Chronicle of Higher Education by Michael Vasquez explains common issues with reporting COVID-19 cases on college and university campuses: inconsistencies across school dashboards, administrations unwilling to report data, and other challenges.
    more K-12 schools content

  • Florida is no longer sending tests to Quest Diagnostics

    This past Tuesday, the Florida Department of Health (DOH) announced that the department would stop working with Quest Diagnostics. Quest is one of the biggest COVID-19 test providers in the nation, with test centers and labs set up in many states. The company claimed in a statement to the Tampa Bay Times that it has “provided more COVID-19 testing on behalf of the citizens of Florida than any other laboratory.”

    So, why is Florida’s DOH cutting ties? Quest Diagnostics failed to report the results of 75,000 tests to the state department in a timely manner. Most of these results were at least two weeks old, and some were as old as April. As all the old results were logged at once on Monday night, Florida’s test and case counts both shot up: nearly 4,000 of those tests were positive.

    Such a reporting delay skews analysis of Florida’s testing capacity over time, especially as many of the backlogged tests were reportedly conducted during the peak of the state’s outbreak in June and July. This delay also likely means that, while the people tested with this batch of tests still received their results in a timely manner (according to Quest), contact tracers and other public health workers were unable to track or trace the nearly 4,000 Floridians who were diagnosed. Such an error may have led to many more cases.

    According to Florida Governor Ron DeSantis, such an error is tantamount to violating state law:

    “To drop this much unusable and stale data is irresponsible,” DeSantis said in a statement Tuesday. “I believe that Quest has abdicated their ability to perform a testing function in Florida that the people can be confident in. As such I am directing all executive agencies to sever their COVID-19 testing relationships with Quest effective immediately.”

    But is cutting all ties with Quest the correct response? Florida’s testing capacity already is below recommended levels. According to the Harvard Global Health Institute, the state has conducted 124 tests per 100,000 people over the past week (August 30 to September 5), with a positivity rate of 13.2%. This per capita rate is far below the state’s suggested mitigation target of 662 tests per 100,000 people, and this test positivity rate is far above the recommended World Health Organization rate of 5%.

    Florida will be able to send many of its tests to state-supported, public testing sites, the Tampa Bay Times reports. Still, this switch will take time and cause additional logistical hurdles at a time when Florida should not be putting the breaks on testing.

    more testing data
  • Three different units for COVID-19 tests

    Three different units for COVID-19 tests

    Colorado is one of six states currently reporting its testing in “test encounters,” a new metric that has appeared in recent weeks. Screenshot of Colorado’s dashboard taken on September 5.

    A few weeks ago, one of my coworkers at Stacker asked me: how many people in the U.S. have been tested for COVID-19?

    This should be a simple question. We should have a national dataset, run by a national public health department, which tracks testing in a standardized manner and makes regular reports to the public. The Department of Health and Human Services (HHS) does run a national testing dataset, but this dataset only includes diagnostic, polymerase chain reaction (PCR) test results, is not deduplicated—a concept I’ll go into more later—and is not widely publicized or cited.

    Meanwhile, 50 state public health departments report their local testing results in 50 different ways. Different departments have different practices for collecting and cleaning their test results, and beyond that, they report these results using different units, or the definitive magnitudes used to describe values.

    You might remember how, in a high school science class, you’d get a point off your quiz for putting “feet” instead of “meters” next to an answer. Trying to keep track of units for COVID-19 data in the U.S. is like that, except every student in the class of 50 is putting down a slightly different unit, no teacher is grading the answers, and there’s a mob of angry observers right outside the classroom shouting about conspiracy theories.

    Naturally, the COVID Tracking Project is keeping track anyway. In this issue, I’ll cite the Project’s work to explain the three major units that states are using to report their test results, including the benefits and drawbacks of each.

    Much of this information is drawn from a COVID Tracking Project blog post by Data Quality Lead Kara Schechtman, published on August 13. I highly recommend reading the full post and checking out this testing info page if you want more technical details on testing units.

    (Disclaimer: Although I volunteer for the COVID Tracking Project and have contributed to data quality work, this newsletter reflects only my own reporting and explanations based on public Project blog posts and documentation. I am not communicating on behalf of the Project in any way.)

    Specimens versus people

    Last spring, when the COVID Tracking Project’s data quality work started, state testing units fell into two main categories: specimens and people.

    When a state reports its tests in specimens, their count describes the number of vials of human material, taken from a nose swab or saliva test, which are sent off to a lab and tested for the novel coronavirus. Counts in this unit reflect pure testing capacity: knowing the number of specimens tested can tell researchers and public health officials how many testing supplies and personnel are available. “Specimens tested” counts may thus be more precise on a day-to-day basis, which I would consider more useful for calculating a jurisdiction’s test positivity rate, that “positive tests divided by total tests” value which has become a crucial factor in determining where interstate travelers can go and which schools can reopen.

    But “specimens tested” counts are difficult to translate into numbers of people. A person who got tested five times would be included in their state’s “specimens tested” count each time—and may even be included six, seven, or more times, as multiple specimens may be collected from the same person during one round of testing. For example, the nurse at CityMD might swab both sides of your nose. Including these double specimens as unique counts may artificially inflate a state’s testing numbers.

    When a state reports its tests in people, on the other hand, their count describes the number of unique human beings who have been tested in that state. This type of count is useful for measuring demographic metrics, such as what share of the state’s population has been tested. In most cases, when states report population breakdowns of their testing counts, they do so in units of people; this is true for at least four of the six states which report testing by race and ethnicity, for example.

    Reporting tests in units of people requires public health departments to do a process called deduplication: taking duplicate results out of the dataset. If a teacher in Wisconsin (one of the “people tested” states) got tested once back in April, once in June, and once this past week, the official compiling test results would delete those second two testing instances, and the state’s dataset would count that teacher only once.

    The problem with such a reporting method is that, as tests become more widely available and many states ramp up their surveillance testing to prepare for school reopening, we want to know how many people are being tested now. As recent COVID Tracking Project weekly updates have noted, testing seems to be plateauing across the country. But in the states which report “people tested” rather than “specimens tested,” it is difficult to say whether fewer tests are actually taking place or the same people are getting tested multiple times, leading them to not be counted in recent weeks’ testing numbers.

    Test encounters

    So, COVID-19 testing counts need to reflect the numbers of people tested, to provide an accurate picture of who has access to testing and avoid double-counting when two specimens are taken from one person. But these counts also need to reflect test capacity over time, by allowing for accurate test positivity calculations to be made on a daily or weekly basis.

    To solve this problem, the COVID Tracking Project is suggesting that states use a new unit: test encounters. The Project defines this unit as the number of people tested per day. As Kara Schechtman’s blog post explains, though this term may be new, it’s actually rather intuitive:

    Although the phrase “testing encounters” is unfamiliar, its definition just describes the way we talk about how many times people have been “tested for COVID-19” in everyday life. If an individual had been tested once a week for a month, she would likely say she had been tested four times, even if she had been swabbed seven times (counted as seven tests if we count in specimens), and even though she is just one person (counted as one test if we count in unique people). In this case, that commonsense understanding is also best for the data.

    To arrive at a “testing encounters” count, state public health departments would need to deduplicate multiple specimens from the same person, but only if those multiple specimens were taken on the same day. “Testing encounters” counts over time would accurately reflect a state’s testing capacity, without any artificial inflation of numbers. And, as a bonus, such counts would align with public understanding of what it’s like to get tested for COVID-19—making them easier for journalists like myself to explain to our readers.

    What is your state doing?

    The COVID Tracking Project currently reports total test encounters for five states—Colorado, Rhode Island, Virginia, New York, and Washington—along with the District of Columbia. Other states may report similar metrics, but have not yet been verified to match the Project’s definition.

    You can find up-to-date information about which units are reported for each state on a new website page conveniently titled, “How We Report Total Tests.” The page notes that the Project prioritizes testing capacity in choosing which state counts to foreground in its public dataset:

    Where we must choose a unit for total tests reporting, we are prioritizing units of test encounters and specimens above people—a change which we believe will provide the most useful measure of each jurisdiction’s testing capacity.

    Also, if you’ve visited the COVID Tracking Project’s website recently, you might have noticed that the state data pages have seen a bit of a redesign, in order to make it clear exactly which units each state is using. Each state’s data presentation now includes all three units, with easy-to-click definition popups for each one:

    Screenshot of the COVID Tracking Project page for New York.

    I recommend checking out your state’s page to see which units your public health department is using for COVID-19 tests, as well as any notes on major reporting changes (outlined below the state’s data boxes). You can read more about the site redesign here.

    When my coworker asked me how many people in the U.S. have been tested for COVID-19, I wasn’t able to give him a precise answer. The lack of standards around testing units and deduplication methods, as well as the federal government’s failure to be a leader in this work, have made it difficult to comprehensively report on testing in America. But if people—and I mean readers like you, not just data nerds like me—make testing units part of their regular COVID-19 conversations, we can help raise awareness on this issue. We can push our local public health departments to standardize with each other, or at least get better about telling us exactly what they’re doing to give us the numbers they put up on dashboards every day.

    more testing data

  • Help advocate for better COVID-19 demographic data

    The COVID Racial Data Tracker, a collaboration between the COVID Tracking Project and the Boston University Center for Antiracist Research, collects COVID-19 race and ethnicity data from 49 states and the District of Columbia. We compile national statistics and compare how different populations are being impacted across the country.

    But there are a lot of gaps in our dataset. We can only report what the states report, and many states have issues: for example, 93% of cases in Texas do not have any reported demographic information, and West Virginia has not reported deaths by race since May 20.

    A new form on the COVID Tracking Project website allows you to help us advocate for better quality data. Simply select your state, then use the contact information and suggested script to get in touch with your governor. States with specific data issues (such as Texas and West Virginia) have customized scripts explaining those problems.

    If you try this out for your state, please use the bottom of the form to let us know how it went!

    MORE STATE DATA

  • What’s up with testing in Texas?

    The COVID Tracking Project published a blog post this week in which three of our resident Texas experts, Conor Kelly, Judith Oppenheim, and Pat Kelly, describe a dramatic shift in Texas testing numbers which has taken place in the past two weeks.

    On August 2, the number of tests reported by Texas’s Department of State Health Services (DSHS) began to plummet. The state went from a reported 60,000 tests per day at the end of July to about half that number by August 12. Conor, Judith, and Pat explain that this overall drop coincides with a drop in tests that DSHS classifies as “pending assessment,” meaning they have not yet been assigned to a county. Total tests reported by individual Texas counties, meanwhile, have continued to rise.

    Although about 85,000 “pending assessment” tests were logged on August 13 to fill Texas’s backlog, this number does not fully add up to the total drop. For full transparency in Texas, DSHS needs to explain exactly how they define “pending assessment” tests, how tests are reclassified from “pending” to being logged in a particular county, and, if tests are ever removed from the “pending” category without reclassification, when and why that happens. As I mentioned in last week’s issue, DSHS has been known to remove Texans with positive antigen tests from their case count; they could be similarly removing antigen and antibody tests reported by counties from their test count.

    If you live in Texas, have friends and family there, or are simply interested in data issues in one of the country’s biggest outbreak states, I highly recommend giving the full post a read. For more Texas test reporting, check out recent articles from Politico and the Texas Tribune.

    more testing data