This page calculates some of the important attributes of the Corona pandemic using data from assumingly reliable sources only. The attributes include country-specific estimates on for example:

  • IFRs
  • Maximum fatalities
  • Fatalities age distribution
  • YPLL
  • Actual number of fatalities
  • Actual number of infections
  • Herd immunity
  • Pandemic status
  • Live PFR
  • Live IFR

The page is updated daily. Latest update: 2023-Feb-03 12:26:15 UTC

How does COVID-19 compare to the flu?

"... Covid, in most populations far less lethal [than the flu] !!!" Is Trump right? How do they compare?

NewsVaccination data has been added, in addition to live IFR and live herd immunity. See the news section below.

Hover the mouse over the columns headings for more information about the content in each column or see the descriptions below the table. Sort by a specific column by clicking a header.

Column descriptions


The population of the selected area/country. The population data is internally stored as sum of persons in 5-year wide age groups, which are linearly interpolated giving an approximate number of persons per year of age. The population data is from 2019.

Some countries are missing due to lack of source data, which is also the reason why the total world population is not 100% correct.

- United Nations (


The calculated generic infection fatality rate (IFR) for each country, assuming a fully unprotected population. The calculation uses data from a research report on the Bergamo infection (see reference), as one of the most infected areas which has been studied thoroughly. The infection rates from Bergamo are then applied to the specific age distribution of each country to calculate these countries' individual overall IFRs.

As of 13 Sep 2020, the report's IFR ranges are linearly interpolated into individual IFR rates for each year of age.

As of 1 Oct 2020, the infection rates from Bergamo are adjusted to compensate for the specific situation that arose in Bergamo. See the News section below.

- How deadly is COVID-19? A rigorous analysis of excess mortality and age-dependent fatality rates in Italy ( )


Health system quality adjusted IFR. See the News section below.

Fatalities, theoretic max

The estimated, approximated theoretical max number of fatalities for each country. The calculation uses the linear interpolation of the healthcare system quality adjusted IFRs, and apply these to each country's population, giving the total number of fatalities for each country. This is as if the whole population got the virus once. (See report mentioned under 'IFR'.)

Fatalities, realistic max

The estimated number of fatalities given that the virus spreads until the population has gained enough immunity until the virus more or less 'burns out' by itself. The calculation assumes that this happens when around 65% of the population has been infected. This number seems to be in line with reports on immunity or protection in heavily infected areas like Bergamo.

This assumes a limited infection period without considering possible reinfections.

Fatalities < 70y (%)

The estimated percentage of calculated fatalities below 70 years for each country, taking each country's age distribution into account.

Fatalities < 50y (%)

The estimated percentage of calculated fatalities below 50 years for each country, taking each country's age distribution into account.

Fatalities < 30y (%)

The estimated percentage of calculated fatalities below 30 years for each country, taking each country's age distribution into account.

Average fatality age

The calculated average age of the fatalities in each country.

Median fatality age

The calculated median age of the fatalities in each country.

YPLL at real. max fatalities

Years of potential life lost is the sum of the estimated remaining life years for the fatalities in each country. (See .) The calculation uses the assumed number of remaining life years for each death, reduced somewhat due to the fact that approx. 98% of all fatalities has at least one comorbidity, and approx. 75% of all fatalities have at least two comorbidities, which would reduce their number of potential live years compared to the average for that age group.

This estimation needs to be improved further. At present it is calibrated and age-adjusted with figures on estimated reduced YPLL for diabetes patients in Canada (reference 2) for the 23% having one comorbidity, and that number squared for the 75% that have two comorbidities.

- WHO - Life tables ( )
- Government of Canada - Chapter 2: Diabetes in Canada: Facts and figures from a public health perspective – Health impact ( )

Avg. YPLL per fatality

The calculated, average number of potential years of life lost per fatality.

Reported fatalities

Number of reported fatalities by Our World in Data. Previously, ECDC were used, but they stopped reporting daily in mid-December 2020.

- European Centre for Disease Prevention and Control ( )

Actual fatalities

This is the estimated actual number of fatalities, taking into account that not all actual fatalities are correctly accredited to COVID-19. This assumption is based on research from the Italian infections, which found that a large portion of the excess deaths might not have been correctly assigned as COVID-19 deaths. This effect seems to be highly age dependent, i.e. the older the subject is, the higher the chance is that the death is not identied as being due to COVID-19. In the oldest age group, one report (see reference) found that the number of excess deaths that were not accredited to COVID-19 were close to equal to the number of identified deaths. In this age group, the number of fatalities were underestimated by 100%.

As of 22 Nov 2020 this calculation was improved and updated. See News section.

The current version of the calculation does not take into account that:

- Wrong reporting on purpose by some authorities
- Different reporting practices in various countries (Belgium is handled specifically).
- The quality of each country's healthcare system and how it affects reporting is very uncertain
- The percentage of missed identification correlates to the age of the subject

- How deadly is COVID-19? A rigorous analysis of excess mortality and age-dependent fatality rates in Italy ( )
- Estimation of excess mortality and life expectancy in the major epicenters of the COVID-19 pandemic in Italy ( )
- Temporal dynamics in total excess mortality and COVID-19 deaths in Italian cities ( )
- European Centre for Disease Prevention and Control ( )

Total infections

The estimated number of infections that is or has been infected with the virus in each country. This is based on the live calculation of the time-dependent IFR and the estimated number of actual COVID-19 fatalities. However, for the world population entry, the number is calculated as the total of the countries in the table. Hence, the number is sligtly lower than when calculated based on the world's generic IFR since some few countries are missing. Infections can happen several times for the same individual, meaning that this figure can grow above the population in the longer run.


The number of vaccine dose injections. Most vaccines require two injections, i.e. 2 doses are required.


Vaccine % of pop

How far the vaccinaiton process has come compared to the total population.

Immunity/protected count

The number persons currently protected by immunity, either by vaccinaiton or a recent infection. Initial immunity that can be present in the population is not considered. It assumes a distribution of the virus propotional to the age distribution.

Pandemic completeness

The current percentage of immunity or protection in the population compared to the immunity level needed for herd immunity. Initial immunity that can be present in the population is not considered.

Live Herd Immunity

The current herd immunity level of the population. See the News section for more details.

Live PFR

The current population fatality rate, i.e. how many percent of the population who have died from covid-19 since the beginning of the pandemic.

Live IFR

The current, forward-looking IFR rate of the population. See the News sections for more details.

Data usage license

Any numbers from this page are free for use by anyone for their own personal or research use. Any use on the web, in the press or media must refer to as the source.

Click to download data in json format


13 Sep 2020:
A linear interpolation method is now applied to both the population age groups from UN and the groups of IFR rates in the Bergamo report. This gives more accurate estimates. Also, some minor rounding errors have been fixed.
30 Sep 2020:
- Added new considerations regarding infection fatality rates to make them more realistic: Now considers the special conditions regarding the Bergamo IFRs. Also consider healthcare system quality in the IFR_hsa column. See this page for more info.
- Added better underestations of fatalities. See this page for more info.
- Some debugging/testing remains, but it is still released here since the calcs seems to be quite correct and in line what would be expected.
- Minor GUI changes.
2 Oct 2020:
- Belgium includes unconfirmed deaths into their reported numbers, which is different from most other countries. Underestimation is fixed to 15% for Belgium. More info on Wikipedia.
- Added current PFR (population fatality rate).
4 Oct 2020:
Added estimated median fatality age.
10 Oct 2020:
- Fixed small bug with IFR healthcare system adjustment.
- Fixed how to summarize infections for the world.
- Added option to show similar data for the 2017-2018 US flu season as a comparison, especially in reference to Trump's statements on lethality. See this page for more info.
8 Nov 2020:
- Changed the estimation of healthcare system quality adjustment: Now it only considers the female life expectancy as part of the ratio estimation, which should give better estimate of the quality of the healthcare system since men do random, stupid things that get them randomly killed a lot more often than women. This slightly affects the IFR and IFR_hsa calculations, and, hence, the estimated number of fatalities and infections.
- Improved how the estimation of infections are calculated: The problem was that using a fixed underestation ratio for a country did not take into consideration how far the country had come into its pandemic process and that the estimations need consider the case when the population is approaching heard immunity levels. Now the underestimation takes into account the distribution between infected and uninfected persons per year of age. The sum of infected plus uninfected persons will converge towards the total number of persons at each year of age. This gives more realistic calculations of infections when the number of infected persons is huge. The most evident example of the effect is Peru.
14 Nov 2020:
Added continent code in parentheses to country name, meaning that you can limit the view to for example just European by using (EU) in the country filter field.
22 Nov 2020:
New and assumingly improved calculations of underestations of fatalities implemented. See this page.
17 Dec 2020:
ECDC stopped delivering daily figures. Statistics on deaths are now from Our World in Data.
24 Jan 2021:
Underestimation now consider improved detection of deaths and virus indentification over time, based on results from the first and second sero survey in India. Also, R0_basic has been adjusted to 3.3 since several report indicate that the original r0_basic was underestimated to begin with, and since new virus mutations seems to be more contagious. This affects the estimated herd immunity level. Lastly, preparations to include vaccinations into the protected and completeness columns have been prepared. Data will be added in some few days.
23 Feb 2021:
Added live IFR, live herd immunity, vaccination data and more. See this page for more details. Results are still preliminary and lacks thorough quality assessment, which will be done up to Mar 1. Also had to change the json file format somewhat.

Last words

This page is developed and maintained by Tor Rune Skoglund. It was made due to frustation from obviously incorrect statements about lethality, infection numbers and death rates made in what are supposed to be reliable media and press. Feel free to contact me at trs at swi dot no with any questions or suggestions.