This week’s update will be brief, both because the Labor Day long weekend makes some of the week’s data less useful and because our team is under additional strain this week due to wildfires and extreme weather.
As was the case with the data following Memorial Day and Independence Day, we are seeing a holiday effect in this week’s topline numbers. All major metrics saw some holiday effect, either from actual decreased testing demand or delayed data reporting, which drives test, case, and death numbers. The total number of tests states reported fell 4 percent in the past week, as the United States continues to test at levels well below the peak of PCR testing reached in late July.
After last week’s stall, cases resumed their decline, falling more than 10 percent from the week prior. We saw more good news as current hospitalizations and deaths both continued to drop. States reported that 5,110 people died of COVID-19 this week in the United States.
The national decline in testing is being driven by the South, where testing appears to be falling most in Florida and Texas, but also in Alabama, Georgia, Louisiana, and Tennessee. As we noted two weeks ago, it is very difficult to understand what is happening with testing. The latest Atlantic story by COVID Tracking Project co-founders Alexis Madrigal and Robinson Meyer addresses the fog that has arisen around testing data, including the eerie absence of visible antigen testing numbers.
We have seen new single-day records for cases across much of the Midwest over the past two weeks—some due to reporting irregularities, some to increased testing, and some due to what appear to be rapidly expanding outbreaks, especially in the Dakotas.
In federal COVID-19 data news, county-level test positivity data is now available, if you happen to click the correct tiny text link on a CMSGov page primarily discussing rules for nursing homes. We visualized this data by location and population for reference, but should note that it is presently unclear what total test units are being used to calculate these test positivity rates, as the federal data does not include data definitions. Using total tests reported in specimens to calculate test positivity rates usually produces much lower rates than using total tests reported in unique people.
In the absence of federal data standards, states report in divergent units and time series, which means that calculating test positivity responsibly requires extreme care with and transparency about testing units and labels. The COVID Tracking Project does not calculate test positivity rates and will not do so until we are confident in our ability to communicate precisely about these complex issues in our visualizations. We urge caution when relying on any (governmental or non-governmental) test positivity calculation that does not transparently and prominently address the question of inconsistent testing units across jurisdictions.
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Erin Kissane is a co-founder of the COVID Tracking Project, and the project’s managing editor.
Peter Walker is Head of Marketing & Growth at PublicRelay and Data Viz Co-Lead at The COVID Tracking Project.
More “Hospitalization and Death Data” posts
20,000 Hours of Data Entry: Why We Didn’t Automate Our Data Collection
Looking back on a year of collecting COVID-19 data, here’s a summary of the tools we automated to make our data entry smoother and why we ultimately relied on manual data collection.
A Wrap-Up: The Five Major Metrics of COVID-19 Data
As The COVID Tracking Project comes to a close, here’s a summary of how states reported data on the five major COVID-19 metrics we tracked—tests, cases, deaths, hospitalizations, and recoveries—and how reporting complexities shaped the data.
How Lagging Death Counts Muddled Our View of the COVID-19 Pandemic
During the worst parts of the COVID-19 pandemic, the United States struggled to keep up with COVID-19 death counts.