Another time-lapse map of the spread of COVID-19 in the United States, this one from David A. West, who posted the above to r/dataisbeautiful on Reddit. This one shows new cases per capita on a county-by-county basis.

Previously: COVID-19 Spreading Across the United States.

Using Johns Hopkins University data, Nicholas Bauer has created this time-lapse map showing the spread of COVID-19 across the United States. This pandemic has been described as having waves; now you can watch them ripple across the continent. [Kottke]

El Confidencial maps COVID-19 mortality rates in Spain at the municipal level; smaller municipalities are not included in the data. [Maps Mania]

Thanks to a combination of low vaccination rates and the COVID-19 Delta variant, intensive care wards are filling up across the United States. The New York Times maps one of the more disturbing metrics of the pandemic: the percentage of occupied ICU beds by hospital region.

Interactive maps produced by Radio-Canada from Montreal Public Health data show where vaccination rates on the Island of Montreal are lagging. The Quebec government’s target is to have at least 75 percent of the population vaccinated. Of the 3,000 sectors on the map, 70 percent have reached that goal for the first dose and 3 percent for the second.

These data are useful in terms of where to target mobile clinics and other vaccination outreach programs. I’d love to see this for other cities in Quebec, especially the one nearest to me: Gatineau’s current rate is relatively low (66.4 percent first dose, 51.2 second dose as of this week) and it’d be revealing to see where the uptake is stronger or weaker.

The latest exhibition at the Osher Map Library and Smith Center for Cartographic Education is deliberately on the nose: Where Will We Go from Here? Travel in the Age of COVID-19 is the Osher’s first crowdsourced exhibition, based in part on more than 140 responses to an online survey about cancelled travel plans and the impact of the novel coronavirus pandemic.

The exhibition is divided into five sections, beginning with an introduction to the mapping of pandemics and diseases, and continuing into four themes that emerged from the types of cancelled or postponed trips our respondents wrote about most frequently: Birthdays, Anniversaries, and Family Milestones; Weddings; Work-Related Travel; and Lost Study-Abroad Experiences. The curators selected stories from the survey and matched personal narratives and reflections about trips not taken to historic maps from our collections. We hope that as you walk through the gallery you will take time to read these personal narratives, and that they provide you with an opportunity to engage in quiet reflection about the challenges you and your loved ones have faced this year, and that you will join us in pondering the question: “Where will we go from here?”

At the end of our questionnaire, we asked participants: “Beyond your canceled travel plans, is there anything else you would like to tell us about how the pandemic has impacted your living and working situations?” We were particularly moved by the honest and thoughtful responses to this question; all responses can be read in a scrolling feed on the monitor at the end of the exhibit.

The physical exhibition opened on 13 May and is open to visitors until 15 October 2021. Free admission with timed tickets; no more than six visitors are allowed in the gallery at any one time. The online exhibition starts here; the sections mixing personal narratives and historical maps can be quite poignant.

A decade after the Geospatial Revolution Project, which explored the use and impact of digital mapping technologies, released its fourth and (apparently) final episode, there’s a new episode focusing on how digital mapping tools were conscripted into the battle against the COVID-19 pandemic. The Project has posted a version of the episode including a live panel discussion afterward on Facebook Live.

Previously: The Geospatial Revolution Project; The Geospatial Revolution Project, Episode Two; The Geospatial Revolution Project, Episode Three; The Geospatial Revolution Project, Episode Four; Maps and the Geospatial Revolution.

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).

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 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]

On February 21 the U.S. reached a grim milestone: half a million deaths due to COVID-19. This NBC News interactive map visualizes the scale of this tragedy with a county-by-county dot map of those deaths, and offers narrative detail in certain places. [Maps Mania]

The New York Times maps the distribution of COVID-19 cases in Los Angeles. “County officials recently estimated that one in three of Los Angeles County’s roughly 10 million people have been infected with Covid-19 since the beginning of the pandemic. But even amid an uncontrolled outbreak, some Angelenos have faced higher risk than others. County data shows that Pacoima, a predominantly Latino neighborhood that has one of the highest case rates in the nation, has roughly five times the rate of Covid-19 cases as much richer and whiter Santa Monica.”

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?)

Alejandro Polanco’s latest Kickstarter project is the Pandemic Atlas. The idea, he says, “is to gather the most relevant information about the pandemics and major epidemics that have hit humanity throughout history to create an atlas in the visual style of my Minimal Geography project.” In 130 pages, the Pandemic Atlas explores major epidemics throughout history, and includes general chapters on heath subjects. The project’s inception actually predates the COVID-19 pandemic; it was initally inspired by the 100th anniversary of the 1918 pandemic, but at the time there was not much interest in the topic. Fast forward today, when an atlas about historical pandemics is just a little too topical.

The Pandemic Atlas Kickstarter runs through 24 February (it’s already met its goal). €20 gets you a digital copy of the atlas, €60 adds the hardcover.

Previously: The Minimal Geography Atlas.

Kenneth Field explores (and dismantles) the mythology around John Snow, the discovery that cholera was spread by water, the role of the famous cholera map and whether it revolutionized disease mapping. Depending on what you know about the subject—if, for example, you got what you know from an episode of Map Men—what you know is more myth than history: the map came after the Broad Street outbreak, it was not by any means the first example of disease mapping, and John Snow wasn’t the map’s cartographer. Field:

The mythology surrounding his work, the 1854 epidemic, and specifically the role of the map are a fine story, but much of it is retold according to the version many seem happy to believe rather than what really happened. But the real story is just as interesting. There are plenty of excellent longer form discussions of the story in which you may be interested. In particular, Kari McLeod’s excellent article that goes into detail about the various myths, and an article by Tom Koch and Kenneth Denike also goes into detail about the true order of events.

Innouveau’s Corona Status Maps are simple yet effective: they show the rate of positive tests at the national, regional, county or city level, depending on the map. They’re animated and have responsive sliders to quickly show how the positivity rate has changed over time; clicking on a region gives a bit more detail as well. With maps of the Netherlands, Amsterdam, the Hague, Rotterdam, the Netherlands plus Germany, Central Europe and Europe, there’s a distinct emphasis in the maps’ focus. [Maps Mania]

Rather than applying restrictions across their entire jurisdictions, several authorities are designating zones to target measures to prevent the spread of novel coronavirus where the spread is at its greatest. Maps can quickly indicate not only where COVID is at its worst, but also where restrictions have been put into place. Two examples: New York City (above left) and the province of Quebec (above right). New York’s map is interactive and has an address search, whereas Quebec’s map is spectacularly ungranular: diagonal lines show that a region has more strict restrictions in some areas but not others, but does not map those areas (which are indicated in text).

The New York Times maps COVID-19 cases at U.S. colleges and universities. The map and searchable database are based on their survey of more than 1,600 post-secondary institutions; the survey “has revealed at least 88,000 cases and at least 60 deaths since the pandemic began. Most of those deaths were reported in the spring and involved college employees, not students. More than 150 colleges have reported at least 100 cases over the course of the pandemic, including dozens that have seen spikes in recent weeks as dorms have reopened and classes have started.”

CovidPulse is an interactive map of COVID-19 trends—both cases and deaths—in the United States. It presents state and county-level data as a series of sparklines, which are very small line graphs. One of the map’s creators, John Nelson, explains all in this video.

Accessible via the WHO’s European COVID-19 dashboard, the European Region COVID19 Subnational Explorer maps the incidence of COVID-19 in Europe on a cases-per-100,000-population basis, with layers showing the 7-day, 14-day and cumulative numbers. The site notes that national public health authorities use different criteria and the numbers are not necessarily usefully comparable. Even so. [Maps Mania]

So which of these two scenarios—careful contrivance or unintentional self-deception—is at play on the Georgia Department of Public Health’s COVID-19 daily status report page?

https://twitter.com/andishehnouraee/status/1284237474831761408

Twitter user @andishehnouraee notes the difference in scale between two county-by-county COVID-19 maps of Georgia. The earlier map maxes out at 4,661 cases per 100,000, the later (and as of this writing, current) map maxes out at 5,165 cases per 100,000. As they point out, there has been a 49 percent rise in total COVID-19 cases between the two maps, but you wouldn’t know it at a glance, because the scales have changed in the meantime.

Is this, as @andishehnouraee suggests, a concerted attempt to hide the severity of the outbreak in Georgia—or, as T. J. Jankun-Kelly thinks might be the case, something that happens when you max out the old scale. In other words: bad faith or bad design? (Or both: it can be both.)

Update 19 Jul: See Twitter threads from Darrell Fuhriman and Jon Schwabish disagreeing with critiques of the Georgia Public Health maps. It’s worth clarifying that only one map is ever viewable at the website: the map’s scale has changed over time, but it’s not like they’re side-by-side except in @andishehnouraee’s tweet.

Update #2: See Jon Schwabish’s blog post critiquing the data visualization critique in more detail.

Wearing a mask in public is increasingly being encouraged or required as a measure to slow the spread of COVID-19. The New York Times maps the rate of mask wearing in the United States. The county-level map is based on more than 250,000 responses to a survey conducted in early July, in which interviewees were asked how often they wore a mask in public.

The map shows broad regional patterns: Mask use is high in the Northeast and the West, and lower in the Plains and parts of the South. But it also shows many fine-grained local differences. Masks are widely worn in the District of Columbia, but there are sections of the suburbs in both Maryland and Virginia where norms seem to be different. In St. Louis and its western suburbs, mask use seems to be high. But across the Missouri River, it falls.

[MAPS-L]

The COVID-19 Event Risk Assessment Planning Tool is a county-by-county map of the U.S. that shows the risk of coming into contact with a COVID-positive individual at an event. “This site provides interactive context to assess the risk that one or more individuals infected with COVID-19 are present in an event of various sizes. The model is simple, intentionally so, and provided some context for the rationale to halt large gatherings in early-mid March and newly relevant context for considering when and how to re-open.” A slider changes the size of the event; risk goes up dramatically with bigger events, of course. Which you’d think would be intuitively obvious. You’d really think so, wouldn’t you. [Cartophilia]

COVD-19 is hitting the United States very hard right now. This interactive map from the Harvard Global Health Institute measures COVID-19 risk at the county level. The four colour-coded risk levels are based on a seven-day rolling average of new COVID-19 cases per 100,000 people: less than one means green (“on track for containment”); more than 25 means red (“tipping point”). It’s explained here. [Matthew Edney]

ArcGIS-based dashboards tracking the spread of the novel coronavirus are now reasonably common, but the first was produced by Johns Hopkins University’s Center for Systems Science and Engineering. As Nature Index reports in this behind-the-scenes look at the JHU coronavirus dashboard, the decision to launch was spur of the moment, but now the dashboard and its underlying data get more than a billion hits every single day, and it is now managed by a team that numbers nearly two dozen. [GIS Lounge]