For weeks, coronavirus cases and deaths have climbed around the world. Now, in many parts of Europe and Asia, authorities believe infections have peaked, prompting them to think about lifting restrictive lockdowns that have shuttered much of the global economy.
The stark figures published by governments each day are difficult to compare across countries. Nevertheless, charts making international comparisons like this one have become a fixture of efforts to describe the growth and scale of the pandemic. This interactive chart allows you to explore data about the pandemic to better understand the disease’s spread and trajectory in countries around the world.
Cases or deaths
Comparing the spread of coronavirus in different countries is difficult using the data being released by governments. Confirmed case counts depend heavily on the extent of countries’ very different testing regimes, so higher totals may simply reflect more testing.
Deaths are somewhat more reliable, but remain problematic because countries have different rules for what deaths to include in their official numbers. The most notable difference between countries’ Covid mortality figures is whether or not they include deaths outside hospitals, particularly in care homes. Some countries like France and the UK have even changed which deaths they include during the course of the epidemic.
For either measure, we use a seven-day rolling average to adjust for the impact of administrative delays to reporting new data over weekends.
Wherever possible we are now reporting excess mortality — the difference between deaths from all causes during the pandemic and the historic seasonal average. This approach suggests the official figures shown here are often significant undercounts. Unfortunately the data needed for this sort of analysis are only available in a few jurisdictions, so the official case or death counts remain the best available data for much of the world.
Logarithmic or linear scales
The vertical axis of our charts are shown using a logarithmic scale, where the same distance on the scale represents multiplying or dividing by the same amount, instead of adding or subtracting the same amount as is the case with a linear scale. Log scales are particularly suited to displaying trends in relative rates of change, like a virus spreading. By comparing the slopes of two lines, a log scale allows us to compare epidemics at a very early stage with those that are much more advanced, even though they have very different absolute numbers of cases or deaths.
On a log scale, an epidemic looks like a steep diagonal line that flattens towards a horizontal line as its rate of growth slows. On the more familiar linear scale, the same data looks like a hockey stick shooting upwards, which gives a better sense of the overall size of each country’s epidemic.
Adjusting for population
Unusually for cross-national data, adjusting for population isn’t strictly necessary when analysing the speed at which a virus spreads. Viruses don’t respect borders, and the rate at which they spread is not affected by the overall population of the affected country.
Population matters least in the early stages of an epidemic because cases are likely to be highly concentrated in particular regions like Hubei or Lombardy. Later, though, viewing the values per million people gives a sense of the pandemic’s relative strain on countries’ resources. Switching to the “per million” view won’t alter the shape of each country’s curve, but will reorder them relative to one another.
Adjusted for population, small countries with broad definitions for what cases or deaths to include in their data will look particularly badly affected, while epidemics concentrated in parts of a very populous country look surprisingly small. Try changing this setting while comparing Belgium to the US or China.
We hide countries with populations under 80,000 to avoid distorting the scale of population-adjusted charts. You can still search from them, though: Try looking at San Marino and Andorra; both European microstates have large proportions of their population affected.
US data in detail
In the United States, the initial response to the virus was hampered mainly by a lack of testing. Since mid-March, lockdowns and social distancing procedures have been largely managed on a state-by-state basis. President Trump has urged governors to use their latitude over reopenings, and several have raced to lift restrictions on business before meeting CDC guidelines on declining case counts as well as the need for widespread testing and contact tracers. But the majority are taking a phased approach to reopening.
Anthony Fauci, the director of the National Institute of Allergy and Infectious Diseases, told the US Senate his biggest concern was that regions of the US would open too soon, triggering a resurgence in the disease and potentially avoidable “suffering and death”. This would also set the economic recovery back in those areas, as they might need to shut down again.
In New York, the epicentre of the disease in the US, the declining number of cases has produced optimism, with the governor allowing a gradual reopening of the less dense areas of the state for some business activity from May 15. All regions in New York must meet a range of CDC criteria that include declining cases of infection and hospitalisations over a set period, as well as certain levels of tracing, before they can reopen.