Vaccine inequity, the ignominy of our times

The global vaccination campaign has been highly regressive, with countries mired in extreme poverty facing the lowest vaccination rates

Since the start of the global vaccination campaign, a total of 15 billion doses have ended up in arms worldwide. But the distribution of these doses has been highly regressive, with the poorest countries receiving the short end of the stick. As it turns out, precisely those countries mired in extreme poverty are also the most vaccine poor. And that is why vaccine inequity is the ignominy of our times.  

Breaking it down

In what follows, we explore the association between extreme poverty rates and vaccine coverage. Let’s break down the visualization into its different components and discuss each briefly in turn.

  • Extreme poverty. The extreme poverty rate on the X axis will capture the share of the population living on less than $1.90 a day at 2011 international prices as per the latest available data point within the last 10 years as published on the World Bank’s PovcalNet. Unfortunately, of the 196 countries in our dataset, 42 lack data on extreme poverty. They represent a total of 396 million people and include 5 LICs (Afghanistan, CAR, Eritrea, North Korea and Syria), 3 LMICs (Cambodia, PNG and Uzbekistan) 14 UMICs and 18 HICs. (Their exclusion should not materially change the results given the strong link between extreme poverty and World Bank income groups and the strongly negative relation between these groups and vaccination progress, as verified for these 42 countries.)
  • Vaccination progress. We will use the total vaccine coverage ratio on the Y axis. “Total” coverage because we account for the 12.8 billion primary doses and the 2.6 billion boosters that have been administered to date. This composite indicator is defined as the sum of adjusted primary doses and booster doses per 100 people. Primary doses have been adjusted to correct for the diversity in vaccine protocols: we put all vaccines on an equal 2-dose footing and multiply doses of 1- and 3-dose vaccines by 2 and 2/3 so that full primary coverage is achieved at 200 doses per 100 people.

The visualization will also show the following variables:

  • Population size. Since the above variables are expressed as a ratio to population, the observations do not convey a sense of scale. To correct for that, we also show the total population size of a country. This will be captured by the size of the bubble shown. The two outliers, China and India, become immediately visible.
  • Country income levels. We also correlate the results with country income levels, where colors will refer to the four income groups of the World Bank income classification: the high, upper-middle, lower-middle and low income countries (HICs, UMICs, LMICs and LICs). The classification approximates the level of development of nations, which will correlate with a host of other characteristics.
  • Time. We will visualize the association between extreme poverty and vaccination dynamically. December 1st, 2020 marks the start date and the visualization runs through to the current date (which should be today, since all data insight posts on pandem-ic are updated daily). To keep the size of the gif down, we let time progress by 14-day intervals. 

To trace out the evolving association between extreme poverty and vaccination, the visualization will also include a regression line.  We could have opted for a linear line weighted by population, but instead are showing a generalized additive model (GAM) smoother. Since we have two giant population outliers which also have for the most part of this pandemic stood out on the vaccination front, a non-linear smoother weighted by population provides a more accurate insight. 

Extreme poverty and total vaccination

Let us now proceed to the results. Below is the dynamic visualization of the association between extreme poverty rates and total vaccine coverage ratios by country, income group and population size. Note that when the gif reaches the last data point (today’s), the visualization labels those countries that have an extreme poverty rate above 10% and a total population above 10 million. A static version of the visualization is copied down below so the country code labels can be read more easily. 

The following results are striking:

  • Despite considerable poverty reduction, extreme poverty remains a pressing problem in so many countries in this world, including several very large ones. As of 2017 – the last reference year for which we have globally comprehensive information –  the world counted just under 700 million extremely poor people. The countries with high extreme poverty rates comprise of LICs, most LMICs as well as a few UMICs, which can be verified by inspecting the horizontal axis together with the colors of the bubbles. 
  • Total vaccination rates vary considerably across the countries that have (all but) eliminated extreme poverty. Check the wide range along the Y-axis among the vertically stacked countries at the 0% value for the X-axis.  Most of the top performers among them are HICs and UMICs. This includes China, which pulls up the population-weighted regression line. 
  • Conversely, and this is the point of this visualization, virtually all countries with non-negligible extreme poverty rates, have lower vaccination rates and have over the course of the pandemic lagged considerably behind. This affects all LICs in the sample (except Rwanda), many LMICs as well as a few UMICs (including South Africa among the larger ones). Note how India pulls up the population-weighted regression line (due to both its large population and its relatively better vaccination performance compared to its peers). But if we exclude India and a few others (Bangladesh, Colombia, Honduras and Nepal) among those labelled with extreme poverty over 10% and a population over 10 million, the sizable vaccination gaps come through very clearly. 

Parting thought

Global vaccination has been highly regressive. The extremely poor are also extremely poorly vaccinated. We observe this to be true at any point in time over the entire course of the pandemic. Initially the primary vaccination campaign was slow to take off in the poorer countries. Momentum in these countries did pick up somewhat later on, but by then the richer ones started rolling out their booster programs. Throughout, total vaccination levels in the poorer countries have remained abysmally low. Even today we continue to see enormous gaps – a topic which is further discussed here

While the speed of vaccine development and diffusion during the COVID-19 pandemic has been without precedent, the situation in the poorest countries – the focus of this post – remains the exception, which is also what makes their predicament an ignominy. Much of the world booked rapid progress, while precisely the poorest of poor countries were left behind. 

This serves as a reminder that the inequities that surfaced during the global vaccination campaign are rooted in deeper inequities in global health and development, which in turn reflect persistent bottlenecks to the aspirations of countries. Unfortunately, yet again, they have shown their ugly face in the vaccine inequity we have observed. An ignominy of our times. 

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