Michigan reports a disproportionate amount of COVID-19 cases and deaths among Black people. But state-level data does not reveal the ways COVID-19 is impacting local communities. To track this, @COVID19Tracking has followed a few cities since end of May. covidtracking.com/blog/state-lev…
Tracking city-level data allows us to see that 48% of Black people who have died from COVID-19 in Michigan are from Detroit. But the decisions that individual jurisdictions make can obscure the scale of this impact.
Wayne County is Michigan’s most populous county. Its data for August 5 shows 13% of the state’s deaths among Black people came from Wayne County. But the county’s data excludes Detroit, which represents 38% of the county’s population.
When we add Detroit back into the equation, it reveals that 60% of Michigan’s COVID-19 deaths among Black people happened in Wayne County. The current reporting system obscures the true impact of COVID-19 within the county, and on the state’s Black population.
Localized analysis will continue to be key in identifying which communities are disproportionately impacted by COVID-19. We plan to release our dataset spanning 64 major metro areas in the near future. It will include ZIP code-level data, along with race and ethnicity data.
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As we’ve seen with many COVID-19 metrics, there’s often a veneer of uniformity obscuring quiet data discrepancies. In this piece, we look at probable COVID-19 case definitions and the decisions states made about how and when to adopt federal guidance. covidtracking.com/analysis-updat…
When states started updating their probable case definitions, as per guidance from the feds, the share of probable cases in their total case counts grew. Our research set out to explore the extent to which this growth was fueled by antigen tests alone.
What we found was that a state’s testing strategy played an important role in shaping probable case counts. States with strong antigen testing programs no longer had to rely on contact tracing and symptom tracking, both difficult to perform at scale.
During the worst moments of the pandemic, the US public health data infrastructure could not keep up with COVID-19 death counts. Our new analysis looks at the effect of reporting lags on death data reported by states and the CDC: covidtracking.com/analysis-updat…
To understand the effect of reporting lags on state COVID-19 death counts, we compared data compiled by the CDC from state dashboards to retrospective data published by some states that charts deaths on the day they actually occurred.
Real-time death counts were affected by both slowness in reporting, which made peaks in deaths appear like they happened later than they did, and by reporting capacity limits, which made deaths look like they peaked lower than they did.
State by state, federal COVID-19 testing data is getting better. Over the last few months, we have observed federal efforts to address many of the dataset’s most pressing problems. covidtracking.com/analysis-updat…
Throughout the pandemic, the federal government has struggled to count COVID-19 tests. Its dataset has long shown signs of infrastructural problems: covidtracking.com/analysis-updat…
Since we last looked at it in February 2021, the federal government has changed its data sourcing for six jurisdictions and corrected submission problems in three, often improving the data greatly.
For most of the project, we’ve been laser-focused on gathering data. We recently began a process to understand *how* our data has been used. Here’s what we found. covidtracking.com/analysis-updat…
Our largely volunteer-run effort became a definitive and trustworthy source for US COVID-19 data and analysis: for media, scientists and medical professionals, academics, and the government.
We became a major data source used by U.S. and international outlets across the political spectrum with more than 7,700 press mentions. We also responded to thousands of media and citizen requests for information on COVID-19 data.
With little guidance from the feds, states have had to make their own decisions about compiling and presenting COVID-19 data, leading to sweeping inconsistencies. Here are some of the key reporting problems we found. covidtracking.com/analysis-updat…
First up: data definitions. More than one year in, many facets of COVID-19 data are still not standardized. States have defined metrics inconsistently, making summaries and comparisons difficult if not impossible.
Next, we look at how states make their data available. Some states report metrics in percentages, without raw numbers. Some provide granular data while others report only summaries. And some states don’t report some metrics at all.
Today we’re releasing research on hospitalization data definitions. Hospitalizations are one of the most critical metrics for understanding the state of the pandemic. covidtracking.com/analysis-updat…
We found that states differ in how they track patients with confirmed COVID-19, suspected COVID-19, or both. We also observed some states lumping metrics, making comparisons difficult.