Maps tracking the progress of the U.S.’s COVID-19 vaccination campaign at the CDC’s COVID Data Tracker (now) include an interactive county-level map showing first and second doses among 12+, 18+ and 65+ populations and a map of vaccine equity (above): a bivariate choropleth map showing the relationship between vaccination coverage and social vulnerability (housing, vehicle access, general poverty).
How this map isn’t nothing but Columbuses and Springfields, I have no idea.
Sam Learner’s River Runner is an amazing visualization that traces the path of a raindrop falling anywhere in the contiguous United States to where it reaches the ocean or leaves U.S. territory. “It’ll find the closest river/stream flowline coordinate to a click/search and then animate along that flowline’s downstream path.” It’s a tad resource-intensive, and if you end up in the Mississippi basin it will take a while (and make clear just how big that river system is), but it’s absolutely transfixing.
This month NOAA updated the official U.S climate normals. You know how in a weather forecast a meteorologist talks about normal temperatures or normal amounts of rain? The climate normals define what normal is: they take into account weather over the past 30 years, and are updated every 10 years. As you might expect, the normals do reveal the extent of climate change.
NOAA compares the new 1991-2020 normals period with the one that came before (1981-2010): “Most of the U.S. was warmer, and the eastern two-thirds of the contiguous U.S. was wetter, from 1991–2020 than the previous normals period, 1981–2010. The Southwest was considerably drier on an annual basis, while the central northern U.S. has cooled somewhat.” (Bear in mind that there’s a 20-year overlap between the two normals.)
The New York Times has created a series of animated maps showing how 30-year normals compare with 20th-century averages for temperature and precipitation. “The maps showing the new temperature normals every 10 years, compared with the 20th century average, get increasingly redder.”
The data is available from NOAA’s website.
This interactive map compares U.S. COVID vaccination rates with active cases at the county level. Created by McKinsey and Company’s COVID Response Center, it’s a bivariate choropleth map that shows two variables at once. (If this confuses you, the legend helps.) It’s a good way to see where low vaccination rates correlate with lots of COVID cases (red on this map), or high vaccination rates with few cases (teal); the map lets you explore other variables as well. [Maps Mania]
The Verge maps the gaps in U.S. broadband coverage. “This map shows where the broadband problem is worst—the areas where the difficulty of reliably connecting to the internet has gotten bad enough to become a drag on everyday life. Specifically, the colored-in areas show US counties where less than 15 percent of households are using the internet at broadband speed, defined as 25Mbps download speed. (That’s already a pretty low threshold for calling something ‘high-speed internet,’ but since it’s the Federal Communications Commission’s standard, we’ll stick with it.)” They’re using anonymized Microsoft cloud data rather than the FCC’s numbers (which don’t have a good track record reflecting real-world speeds).
The Centers for Disease Control and Prevention released data and maps showing the estimated rate of COVID-19 vaccine hesitancy in the U.S. on a county-by-county basis. The data is based on a question in the Census Bureau’s Household Pulse Survey that asked respondents whether they’d get a vaccine for COVID-19 once it was available to them. Methodology and datasets here. [Boston.com]
The New York Times maps partisan sorting in America—the tendency for voters to self-select into areas where people think and vote the same way they do—down to the neighbourhood level.
The maps above—and throughout this article—show their estimates of partisanship down to the individual voter, colored by the researchers’ best guess based on public data like demographic information, voter registration and whether voters participated in party primaries.
We can’t know how any individual actually voted. But these maps show how Democrats and Republicans can live in very different places, even within the same city, in ways that go beyond the urban-suburban-rural patterns visible in aggregated election results.
It goes beyond racial, urban vs. suburban vs. rural and house vs. apartment splits, to the point where researchers are wondering whether Americans are “paying attention to the politics of their neighbors” when they decide where to live. This has implications not only in terms of electoral targeting (e.g. gerrymandering, voter suppression), but in terms of basic social cohesion.
The maps are based on research by Jacob R. Brown and Ryan D. Enos published earlier this month in Nature Human Behavior.
Previously: Red and Blue vs. Gray and Green.
Writing at The Conversation, geographers Derek Alderman and Joshua Inwood explore African American examples of “counter-mapping,” from maps made by the Black Panthers proposing new police districts to modern interactive maps of lynchings and police violence. “Black Americans were among the earliest purveyors of counter-mapping, deploying this alternative cartography to serve a variety of needs a century ago.” [Osher]
Previously: ‘Counter-Mapping’ the Amazon.
Kenneth Field has released a dasymetric dot density map of the 2020 U.S. presidential election results. One dot equals one vote. “Data at a county level has been reapportioned to urban areas. Dots are positioned randomly.” It’s in the same vein as his 2016 map, which went all kinds of viral when he posted it in early 2018. A high-resolution downloadable poster is here; an interactive version is here.
The New York Times maps the risk of getting COVID-19 in the United States on a county-by-county basis (previously: Mapping COVID-19 Exposure Risk at Events). [Maps Mania]
Now that vaccines are available, they can be mapped as well. The U.S. Centers for Disease Control’s COVID Data Tracker includes this map of total doses administered in the U.S.; this NBC News county-level map showing the percentage of Americans living within 50 miles of a pharmacy expected to carry a vaccine dates from December and is probably out of date by now. [Maps Mania]
According to a survey, more than a quarter of the U.S. population would not get a COVID-19 vaccine if it was available to them. This number is not evenly distributed: this map from MIT Technology Review, presented as a map showing whether your neighbours want to get vaccinated, reveals the regional pockets of vaccine hesitancy (see above). (What the actual hell, Louisiana?)
xkcd did another map thing, so I have to post about it; it’s a rule. This time Randall revisits the design of the map he did for the 2016 U.S. presidential election, in which one figure represents 250,000 votes for each candidate. In a Twitter thread, he explains the rationale for the map:
It tries to address something that I find frustrating about election maps: Very few of them do a good job of showing where voters are. […] There are more Trump voters in California than Texas, more Biden voters in Texas than New York, more Trump voters in New York than Ohio, more Biden voters in Ohio than Massachusetts, more Trump voters in Massachusetts than Mississippi, and more Biden voters in Mississippi than Vermont.
Previously: xkcd’s 2016 Election Map.
The thing that seems to worry authorities most about COVID-19 is its potential to overwhelm hospitals, at which point the mortality rate really begins to shoot up. In March, the University of Minnesota’s Carlson School of Management released the COVID-19 Hospitalization Tracking Project, which maps, on a county-by-county, basis, the percentage of hospital and ICU beds occupied by COVID-19 patients. [Maps Mania]
The thing about this xkcd cartoon is that at first glance it’s entirely plausible: Randall has done violence to state boundaries while maintaining the rough overall shape of the lower 48. He’s snipped out seven states without anyone noticing if they don’t look too closely.