Global coronavirus cases and deaths have climbed again since the beginning June. The centre of the pandemic has shifted to Latin America, while authorities in many parts of Europe and Asia believe infections have peaked, prompting them to begin lifting restrictive lockdowns that have shuttered much of the global economy.
Governments’ stark daily figures are difficult to compare across countries, and may be significant undercounts. But the data needed to analyse the more reliable and comparable excess mortality metric are only available in a few jurisdictions, leaving these official case and death counts the best available data for much of the world.
US states in detail
New infections have risen sharply in many US states in recent weeks, prompting state governments and businesses to slow their easing of lockdown measures. Twenty-five states reported record seven-day averages in new confirmed cases in the week to July 7, FT analysis of data compiled by the Covid Tracking Project shows.
Since mid-March, lockdowns and social distancing procedures have been largely managed on a state-by-state basis. President Trump urged governors to use their latitude over reopenings, and several had 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.
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. Between May 25 and July 3, Spain’s data was not readily comparable to its earlier figures, and was temporarily removed from the chart until a revised time series was published.
For either measure, we use a seven-day rolling average to adjust for the impact of administrative delays to reporting new data over weekends.
The FT is tracking excess mortality — the difference between deaths from all causes during the pandemic and the historic seasonal average — in the handful of countries and municipalities that publish suitably recent data, and has reported on the specific circumstances in Mexico, Russia, South Africa, Turkey and the UK."
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.
Unless otherwise stated below, national data comes from the European Centre for Disease Prevention and Control.
Data for the United States, Puerto Rico, Guam, American Samoa, the US Virgin Islands and Northern Mariana Islands come from The Covid Tracking Project. Data for New York state has been adjusted to redistribute nursing home deaths that were added to the official death toll on May 7 in proportion to its original data. Data for New Jersey has been adjusted to redistribute 1,854 probable Covid-19 deaths that were added to the official death toll on June 25 in proportion to its original data. To improve comparability with other countries on the daily death toll chart, the US data on the cross-national chart has been adjusted to begin displaying seven days after first averaging three daily deaths. During this period, there was a localised outbreak of Covid-19 in Washington state.
UK data comes from the UK Department of Health and Social Care. Deaths data prior to August 13 is a revised time series (CSV) using a new defintion of Covid deaths as those which occurred within 28 days a positive test. On July 2, the UK’s methodology for reporting positive cases changed to remove 30,302 duplicates identified when combining testing data from hospitals (“pillar 1”) and private sector labs (“pillar 2”). Since that date, the data comes from the revised time series (CSV) published by the DHSC. Prior to July 2, UK case data are the sum of the revised totals published by Public Health England, Public Health Scotland, Public Health Wales, and the Northern Ireland Department of Health.
On September 6, Bolivia added 1,610 deaths to its official cumulative death toll without explaination. The time series up until that date has been adjusted to redistributed these deaths in proportion to the previously known distribution of the data.
On September 6, Ecuador adjusted its methodology to cease distinguishing betwween confirmed and suspected Covid-19. This resulted in 3,752 additonal deaths previously classified as suspected being added to its official cumulative death toll. The time series up until that date has been adjusted to redistributed these deaths in proportion to the previously known distribution of the data.
Data for Italy before August 17 has been adjusted to redistribute 154 deaths from March, April and May that the Parma Local Health Authority had not previously reported. These have been distributed in proportion to the previously-known data for the Emilia-Romagna region in those three months.
Data for Peru before July 23 has been adjusted to redistribute 3,688 deaths added in a revision on July 22 and 3,658 deaths added in a revision announced on August 13. Both adjustments distributed the additional deaths in proportion to the previously available data.
Data for Chile before July 18 has been adjusted to redistribute revised death totals published on June 6 and July 16, and the addition of previously unreported cases added on June 17, all in proportion to the original data.
Deaths data for Spain before July 3 comes from revisions published by the Spanish Ministry of Health. 209 deaths that could not be attributed to a specific date have been distributed uniformly across the remaining distribution.
Data for India before June 16 has been adjusted to redistribute older deaths added on that date by Maharashtra and Delhi, in proportion to its original data.
Data for China from before April 17 has been adjusted to redistribute a data revision published on that day in proportion to its original data.
Data for France has been adjusted to redistribute nursing home deaths that were added to the official death toll on April 2 as well as revised confirmed case counts on May 5 and May 28, in proportion to its original data.
Unless otherwise stated, population figures come from the World Bank. Population data for Anguilla; Bonaire, Sint Eustatius and Saba; the Falkland Islands, and Western Sahara come from the United Nations Population Division. Data for Eritrea comes from the World Health Organisation. Local sources are used for: Cyprus, Guernsey, Jersey, Moldova, Taiwan, the United Kingdom, the United States and Vatican City.
Help us improve these charts: We are looking for further sources of national or municipal mortality data showing total deaths from all causes, preferably broken down by day or week and including figures for recent weeks. If you know of a source of this data for your area, please email email@example.com.
US reporting: Brooke Fox
Editing: Martin Stabe