Johns Hopkins Data

The first visualisations use data from Johns Hopkins University. They are designed to help analyse the trends in COVID-19 activity reported by different countries. Note many countries do not detail recoveries from illness although the vast majority of cases do recover.

The data will be updated once per day at 0900 UTC. Please read the caveats on using this data explained below.


  1. The reported data is subject to delays in aggregation and completeness.
  2. There are varying levels of detail from different authorities and this variability may compound as the outbreak proceeds.
  3.  Countries which experience surges in suspected cases of COVID-19 may be unable to test all suspected cases.
    1. Some countries have prioritised the testing of only the severely ill and hospitalised patients.
    2. The number of infections in the community in these countries may be higher than officially reported.
  4. Most people do recover from COVID-19 but most countries are no longer reporting the number of people who have recovered from illness.
  5. Direct comparison between countries at different levels of activity may give rise to erroneous conclusions.

European Centre for Disease Prevention and Control data

The following visualisations have been created by the team at Our World In Data, using data from the European Centre for Disease Prevention and Control. This  data is refreshed daily at around 1300hrs UTC.

This chart compares the rates of new cases each day to determine how fast the outbreak is growing in different countries. Note that you can toggle between logarithmic axes (default) and linear axes. Note that the straight lines indicate the time taken for cases to double in size. Singapore and Japan have taken around 10 days for their case numbers to double, contrasting sharply with Turkey, Iran and Italy which had very sharp increases in the early stages of their outbreaks. South Korea also had a very sharp increase in cases but this has rapidly tailed off over time as their social distancing policies have dramatically reduced transmission.

In the charts below:

  • You can click LOG (at the end of each axis) to toggle between logarithmic and linear scales for the X- and Y- axes.
  • Data is downloadable and the sources are linked.
  • You can also use Select countries to compare a smaller number of locations.


In comparing the rising number of cases reported in different countries, it is important to consider the number of tests being carried out. Put simply, if you don't look for the disease, you don't know if it is there or not. Charts describing the number of tests performed by each country include comparisons between the number of cases against the number of tests performed. Again, the axes can be toggled between logarithmic (default) and linear scales.


When considering comparisons between countries of widely varying populations, it is good practice to "normalise" the comparisons by dividing the raw data by the population size to get a more accurate representation of the data.

In the graph below, the number of tests carried out is charted against the total number of people infected with COVID-19, both of which have been normalised to the population sizes.

Take the example of Faeroe Islands, a small archipelago of islands midway between Scotland and Iceland. By 20 March, Faeroe Islands had detected 72 cases and had performed over 1,640 tests. But this is for a population of around 49,000 people, meaning that over 3% of the islands' population has been tested by this date.

This graph shows the relative amount of testing done in each country if we assume that they each have a population of 1 million people and with the number of cases and tests scaled appropriately. Smaller populations may appear to carry out more testing than larger populations in the early stages of the outbreak because a small increase in tests carried out means a larger proportion of their population has been tested than if the same number of tests were carried out in countries with much larger populations.