Demystifying COVID-19 Vaccination Charts
By: Amanda Makulec
Tags: Public Health, Data Visualization, Covid 19, Communications Planning, Dataviz

If you skip the rest of this article about the nuances and complexities of vaccination data, please remember this: all of the prevention measures (masks, distancing, hand washing) that we’re practicing now need to be part of our lives for the foreseeable future, particularly with new COVID-19 variants in circulation.

Listen to public health officials. Be hopeful and excited for this huge scientific milestone, but also remember, we still don’t have sound data on whether full vaccination prevents you from acquiring and transmitting the SARS-nCoV2 virus to others, even if you yourself don’t get sick.

For a year, we unpacked the complexity of COVID-19 case data.

Over the last year, there’s been a collective learning about the complexity of COVID-19 case data in the data visualization community.

What seemed like straightforward numbers (infections, recoveries) on the surface required more nuanced understanding, including factors like data collection methods, related metrics like the complicated test positivity rate, and the predictable peaks and valleys routine in health information reporting

I’ve developed charts of immunization coverage data many times while working on global health programs. Immunization experts corrected my missteps and helped me better understand uncertainty, denominator challenges, and data quality issues to monitor in coverage numbers. Vaccination data gets even more complex with multi-dose vaccines. As data journalists, health departments, and other sites launch trackers, the focus seems to be on the cheery cumulative climb of the ‘doses administered’ curve, which tells an incomplete story.

We can collectively benefit from becoming more informed readers (and creators, with the appropriate subject matter expertise) of data visualizations about immunization as COVID-19 vaccination trackers spin up. Here are nine considerations when reading or creating charts of COVID-19 vaccination data.

Nine Considerations When Reading or Creating Charts of COVID-19 Vaccination Data

1. Don’t fixate solely on the endless climb of the cumulative ‘doses administered’ line chart.

The total doses administered feels like a vanity metric — or at least only one part of a more complicated puzzle. Yes, we want to see the line keep climbing. But who is receiving those doses? What share of the total available doses in that state have been administered? How many people are fully immunized (two shots, with the current regimen) compared to those partially immunized?

In some trackers, the total doses is normalized to doses per 100 people in a country or state. While doses per population can help us compare vaccine rollout across countries or states, having two-dose vaccine regimens, and eventually a mix of single- and multi-dose vaccines, will make doses a poor proxy for coverage — which is really what we’re trying to understand.

2. Clearly identify benchmarks and goals to aid understanding, but recognize those benchmarks are likely to change.

Why do we care so much about calculating coverage? The percent of the population fully vaccinated is the metric we compare to the ‘herd immunity’ thresholds, making this metric the number that will be used in debates about reopening timelines. Make reopening decisions too early, when vaccination coverage is still low and community spread is high, and there could be real life or death consequences to those choices.

Herd immunity thresholds vary depending on the disease. Estimates for herd immunity necessary to curb the spread of COVID-19 currently range from 75% to 90%, but estimates are still being adjusted as we learn more. Current estimates of a herd immunity threshold are based on what data we have about COVID-19 — and if you’ve been following the disease over the past year, you’ve seen that there’s much we’re still learning. Discussing the upward shift in estimates (which started out at 60–70%), Marc Lipsitch, an epidemiologist at Harvard’s T.H. Chan School of Public Health, said, “You tell me what numbers to put in my equations, and I’ll give you the answer…but you can’t tell me the numbers, because nobody knows them.”

Vaccine coverage does not account for those who have recovered from COVID-19 and may have immunity from the virus (having had COVID-19 does not disqualify you from receiving the vaccine). Deduplicating the number of ‘immune’ persons would be exceedingly complex, which is why you’ll see vaccine coverage used as a proxy for comparison against the herd immunity threshold.

The herd immunity estimated benchmarks can also be helpful for interpreting vaccine acceptance data. Reading the trend chart below, the shaded band (representing a range, rather than a specific threshold) spans from 75% to 90%, since a precise number hasn’t been established. Ideally the green area (‘definitely yes or probably yes will take the COVID-19 vaccine’) would exceed the lower bound of that reference band, indicating that at least enough people would be willing to take a COVID-19 vaccine to meet the minimum threshold.