In the midst of a constantly evolving pandemic like COVID-19, it is not a simple matter to identify countries that have been most effective and therefore have the most to teach the rest of the world about best practices. Based on the current data, Exemplars in Global Health (EGH) developed a methodology to help identify these emerging successful countries. There are considerable limitations to the selection methodology due to the evolving nature of the pandemic including incomplete data, evolving case definitions, and the fact that the ultimate outcomes are unknown.
As you will see, it is not possible to identify emerging success stories, or exemplars, using just one indicator. Each data point has nuanced drivers and meanings, making it important to triangulate and look across multiple indicators to identify countries that have had success to date in managing the pandemic. The daily rates of confirmed deaths follow very different trajectories in countries. The steeper the slope of the curve, the faster the rate of increase in deaths. Countries at the top of the first graph below have had the most deaths, but some of those countries also have larger populations.
The second graph below shows deaths per capita to account for differences in population. These graphs suggest that some responses have been much more effective at reducing deaths from COVID-19 than others, but they do not tell us why they are more effective.
Detection Indicators
EGH selected three indicators for the detection phase, all of which are measured relative to population size: tests per capita, tests per confirmed case, tests per confirmed deaths.
The graph below shows the total number of COVID-19 tests performed per thousand people by country. Perhaps the biggest challenge in thinking about testing is that the number of tests performed depends on a country’s testing strategy—that is, how many people a country intends to test given its context. More tests is not necessarily better if, for example, a country has made a decision to focus on containment measures that do not require blanket testing.
In the early stages of an outbreak, containment may be possible by testing frequently to identify cases and trace contacts. However, once community transmission is widespread and containment is no longer possible, population-wide measures to reduce transmission are less dependent upon testing. If these measures are successful in reducing the spread, then case finding and contact tracing eventually become feasible again, and widespread testing again becomes critical.
The bar graph below shows the average number of tests performed per confirmed case. Countries with the highest ratio of tests to confirmed cases are likely to have a more accurate understanding of how many total (not just confirmed) cases they have.
Some testing strategies focus on high-risk groups such as health care workers or high-risk locations such as nursing homes. Strategies that focus on those at the highest risk will result in a lower number of tests performed per confirmed case, meaning countries will know less about of the true magnitude of the outbreak in the community at large.
The graph below shows the total number of tests performed and the total number of confirmed deaths, per million people in a country. In general, a high number of tests per death is preferable because it indicates widespread testing and assessment of community transmission.
Considering the context, however, is especially important to ensure we are aware of what the data can and cannot tell us. In very large countries, for example, the evolution of the epidemic may vary across different cities and regions. Some outbreaks may be successfully contained, whereas others are not.
The graph below shows the total number of confirmed COVID-19 cases per million people. The number of cases, however, are dependent on a country’s testing capacity and strategy. Low numbers of cases could reveal successful containment or they could indicate an inability or choice not to test widely.
The graph below shows the total number of COVID-19 cases per million people and the doubling time of cases. A longer doubling time indicates a lower rate of transmission. The doubling time is less dependent on testing capacity as long as the capacity does not change over time—which it often does. We would consider a country with few confirmed cases and a long doubling time to be successfully containing the outbreak, although low testing capacity could still be a factor. In many cases a long doubling time may suggest that containment measures are starting to take effect. On the other hand, few cases and a short doubling time may suggest that the outbreak is spreading quickly, and the number of cases is set to increase.
Country Selection
In early May 2020, EGH surveyed the countries that appeared to be controlling the outbreak by each indicator and phase as discussed above. Once EGH had the quantitative results, they also considered diversity and representativeness (e.g., demographics, form of government, geographic features, or global region).
As a result of this analysis, EGH has selected three countries as exemplars to study in greater depth: Germany, South Korea, and Vietnam. This framework identified these three countries as they provide key success stories in addressing the pandemic.
Source and references | ourworldindata.org – Cover Photo | Pixabay
