Politicising Vaccinations

Yesterday I wrote my usual weekly piece about the progress of the Covid-19 pandemic in the five states I cover. At the end I discussed the progress of vaccinations and how Pennsylvania, Virginia, and Illinois all sit around 25% fully vaccinated. Of course, I leave my write-up at that. But not everyone does.

This past weekend, the New York Times published an article looking at the correlation between Biden–Trump support and rates of vaccination. Perhaps I should not be surprised this kind of piece exists, let alone the premise.

From a design standpoint, the piece makes use of a number of different formats: bars, lines, choropleth maps, and scatter plots. I want to talk about the latter in this piece. The article begins with two side by side scatter plots, this being the first.

Hesitancy rates compared to the election results

The header ends in an ellipsis, but that makes sense because the next graphic, which I’ll get to shortly, continues the sentence. But let’s look at the rest of the plot.

Starting with the x-axis, we have a fairly simple plot here: votes for the candidates. But note that there is no scale. The header provides the necessary definition of being a share of the vote, but the lack of minimum and maximum makes an accurate assessment a bit tricky. We can’t even be certain that the scales are consistent. If you recall our choropleth maps from the other day, the scale of the orange was inconsistent with the scale of the blue-greys. Though, given this is produced by the Times, I would give them the benefit of the doubt.

Furthermore, we have five different colours. I presume that the darkest blues and reds represent the greatest share. But without a scale let alone a legend, it’s difficult to say for certain. The grey is presumably in the mixed/nearly even bin, again similar to what I described in the first post about choropleths from my recent string.

Finally, if we look at the y-axis, we see a few interesting decisions. The first? The placement of the axis labels. Typically we would see the labelling on the outside of the plot, but here, it’s all aligned on the inside of the plot. Intriguingly, the designers took care for the placement—or have their paragraph/character styles well set—as the text interrupts the axis and grid lines, i.e. the text does not interfere with the grey lines.

The second? Wyoming. I don’t always think that every single chart needs to have all the outliers within the bounds of the plot. I’ve definitely taken the same approach and so I won’t criticise it, but I wonder what the chart would have looked like if the maximum had been 35% and the grid lines were set at intervals of 5%. The tradeoff is likely increased difficulty in labelling the dots. And that too is a decision I’ve made.

Third, the lack of a zero. I feel fairly comfortable assuming the bottom of the y-axis is zero. But I would have gone ahead and labelled it all the same, especially because of how the minimum value for the axis is handled in the next graphic.

Speaking of, moving on to the second graphic we can see the ellipsis completes the sentence.

Vaccination rates compared to the election results

We otherwise run into similar issues. Again, there is a lack of labelling on the x-axis. This makes it difficult to assess whether we are looking at the same scale. I am fairly certain we are, because when I overlap the graphics I can see that the two extremes, Wyoming and Vermont, look to exist on the same places on the axis.

We also still see the same issues for the y-axis. This time the axis represents vaccination rates. I wish this graphic made a little clearer the distinction between partial and full vaccination rates. Partial is good, but full vaccination is what really matters. And while this chart shows Pennsylvania, for example, at over 40% vaccinated, that’s misleading. Full vaccination is 15 points lower, at about 25%. And that’s the number that needs to be up in the 75% range for herd immunity.

But back to the labelling, here the minimum value, 20%, is labelled. I can’t really understand the rationale for labelling the one chart but not the other. It’s clearly not a spacing issue.

I have some concerns about the numbers chosen for the minimum and maximum values of the y-axis. However, towards the middle of the article, this basic construct is used to build a small multiples matrix looking at all 50 states and their rates of vaccination. More on that in a moment.

My last point about this graphic is on the super picky side. Look at the letter g in “of residents given”. It gets clipped. You can still largely read it as a g, but I noticed it. Not sure why it’s happening, though.

So that small multiples graphic I mentioned, well, see below.

All 50 states compared

Note how these use an expanded version of the larger chart. The y-minimum appears to be 0%, but again, it would be very helpful if that were labelled.

Also for the x-axis in all the charts, I’m not sure every one needs the Biden–Trump label. After all, not every chart has the 0–60% range labelled, but the beginning of each row makes that clear.

In the super picky, I wish that final row were aligned with the four above it. I find it super distracting, but that’s probably just me.

Overall, this is a strong piece that makes good use of a number of the standard data visualisation forms. But I wish the graphics were a bit tighter to make the graphics just a little clearer.

Credit for the piece goes to Danielle Ivory, Lauren Leatherby and Robert Gebeloff.

Vaccinate Me, Baby, One More Time

With the rollout of the first vaccination programme in the United Kingdom, the BBC had a helpful comparison table stating the differences between the four primary options. It’s a small piece, but as I often say, we don’t necessarily need large and complex graphics.

A nice little comparison table

Since there are only four vaccines to compare and only a handful of metrics, a table makes a lot of sense.

But I wanted to take it a step further and so I threw together a quick piece that showed some of the key differences. In particular I wanted to focus on the effectiveness, storage temperatures (key to distribution in the developing world), and cost.

My quick take

You can pretty quickly see why the United Kingdom’s vaccine developed by Oxford University and produced by AstraZeneca is so crucial to global efforts. The cost is a mere fraction of those of the other players and then for storage temperature, along with Russia’s Sputnik vaccine, it can be stored at common refrigerator temperatures. Both Pfizer’s and Moderna’s need to be kept chilled at temperatures beyond your common freezer.

And in terms of effectiveness, which is what we all really care about, they’re fairly similar, except for the Oxford University version. Oxford’s has an overall effectiveness of 70%. (In)famously, it exhibited a wide range of effectiveness during trials of between just over 60% and 90%.

The 60-odd% effectiveness was achieved when using the recommended dosage. However, in one small group of trial participants, they erroneously were given a half-dosage. And in that case, the dosage was found to be far more effective, approximately 90%. And this is why we would normally have longer, wider-ranging trials, to dial in things like doses. But, you know, pandemic and we’re trying to return to some sense of normalcy in a hurry.

All that said, Oxford’s will be crucial to the developing world, where incomes and government expenditures are lower and cold-storage infrastructure much less, well, developed. And we need to get this coronavirus under control globally, because if we don’t, the virus could persist in reservoirs, mutating for years until the right mutation comes along and the next pandemic sweeps across the globe.

I know we’re presently all fighting about wearing masks, but when we get to having vaccines available to the public, let’s really try to not make that a political issue.

Credit for the original piece goes to the BBC.

Credit for my piece goes to me.

How Would the Covid-19 Vaccines Work

Over the last week or so, we have been receiving some encouraging news from the makers of three viable Covid-19 vaccines: Pfizer, Moderna, and AstraZeneca. All three have reported their vaccines as at least 90% effective. This doesn’t mean the relevant regulatory agencies have verified that data, but it’s better than injecting ourselves with bleach.

Keep this in mind, though, a full vaccination roll out will take months. Having 20–40 million doses is great, but the population of the United States is 330 million. The expectation is a return to normalcy will not really begin until the end of Q3 or beginning of Q4 2021.

This article from the Washington Post does a good job of explaining some of the next steps—and some of the significant logistical hurdles. They illustrate part of the process of shipping the Pfizer vaccine, which needs to remain cooled -70ºC. That’s -94ºF. A wee bit colder than most normal freezers operate.

The Post article also illustrates how the Pfizer/Moderna type of vaccine works—the Pfizer and Moderna tackle it one way whilst AstraZeneca tackles it via a second method.

The first steps in the process.

There’s a lot going on here, but I like the simplified approach the designers took. This whole situation is complicated, but here we see the process distilled to its most essential elements. And the restrained use of colour helps tremendously.

The vial and then needle are filled red, and that red colour carries through into the messenger RNA (mRNA) that is absorbed by the cells and ultimately creates the spike proteins used by the virus (not the virus itself).

Credit for the piece goes to Carolyn Y. Johnson and Aaron Steckelberg.

The Vaxx Path

Today we look at a wee graphic from the BBC examining the current state of Covid-19 vaccines. None have been approved, but 163 are on the path to approval.

The vaxx path

This falls into the category of not everything has to be super complex. Each vaccine is shown as a discrete unit, a small square. For me in this instance this works better than a bar chart showing the total number per each phase. It highlights how each vaccine is a distinct unit and that it can move from one section down to the next. (Although I suppose if it fails a phase it can also be removed entirely.)

And if you want another reason why a nationalist, isolationist foreign policy that bashes foreign countries is not great…none of the Phase 3 candidates, closest to approval, are from an American company or institution.

Credit for the piece goes to the BBC graphics department.