As of January 6, 2022, an average of 1,192 people per day have died from COVID-19 in the U.S. since the first case was confirmed in the country on January 20th the year before. On an average day, nearly 8,000 people die from all causes in the United States, based on data from 2019. Based on the latest information, roughly one in seven deaths each day were related to COVID-19 between January 2020 and January 2022. However, there were even days when more than every second death in the U.S. was connected to COVID-19. The daily death toll from the seasonal flu, using preliminary maximum estimates from the 2019-2020 influenza season, stood at an average of around 332 people. We have to keep in mind that a comparison of influenza and COVID-19 is somewhat difficult. COVID-19 cases and deaths are counted continuously since the begin of the pandemic, whereas flue counts are seasonal and often less accurate. Furthermore, during the last two years, COVID-19 more or less 'replaced' the flu, with COVID-19 absorbing potential flu cases. Many countries reported a very weak seasonal flu activity during the COVID-19 pandemic. But it has yet to be seen how the two infectious diseases will develop side by side during the winter season 2021/2022 and in the years to come.

Symptoms and self-isolation COVID-19 and influenza share similar symptoms – a cough, runny nose, and tiredness – and telling the difference between the two can be difficult. If you have minor symptoms, there is no need to seek urgent medical care, but it is recommended that you self-isolate, whereas rules vary from country to country. Additionally, rules depend on someone's vaccination status and infection history. However, if you think you have the disease, a diagnostic test can show if you have an active infection.

Scientists alert to coronavirus mutations The genetic material of the novel coronavirus is RNA, not DNA. Other notable human diseases caused by RNA viruses include SARS, Ebola, and influenza. A continual problem that vaccine developers encounter is that viruses can mutate, and a treatment developed against a certain virus type may not work on a mutated form. The seasonal flu vaccine, for example, is different each year because influenza viruses are frequently mutating, and it is critical that those genetic changes continue to be tracked.

This dataset contains counts of deaths for California counties based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in each California county regardless of the place of residence (by occurrence) and deaths to residents of each California county (by residence), whereas the provisional data table only includes deaths that occurred in each county regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

In 2024, about **** million deaths were reported in the United States. This reflected a slight decrease from the previous year, and an ** percent decrease from the peak of the COVID-19 pandemic in 2020.

The leading causes of death by sex and ethnicity in New York City in since 2007. Cause of death is derived from the NYC death certificate which is issued for every death that occurs in New York City.

Real-time data on deaths per day worldwide

As of May 31, 2025, 13,341 civilian deaths in Ukraine were reported by the Office of the United Nations High Commissioner for Human Rights (OHCHR) due to the Russian invasion that started on February 24, 2022. OHCHR specified that the real figures could be significantly higher. Furthermore, the increases in the figures each week should not be attributed to that week only because they include adjustments from previous weeks.

This dataset contains counts of deaths for California as a whole based on information entered on death certificates. Final counts are derived from static data and include out-of-state deaths to California residents, whereas provisional counts are derived from incomplete and dynamic data. Provisional counts are based on the records available when the data was retrieved and may not represent all deaths that occurred during the time period. Deaths involving injuries from external or environmental forces, such as accidents, homicide and suicide, often require additional investigation that tends to delay certification of the cause and manner of death. This can result in significant under-reporting of these deaths in provisional data.

The final data tables include both deaths that occurred in California regardless of the place of residence (by occurrence) and deaths to California residents (by residence), whereas the provisional data table only includes deaths that occurred in California regardless of the place of residence (by occurrence). The data are reported as totals, as well as stratified by age, gender, race-ethnicity, and death place type. Deaths due to all causes (ALL) and selected underlying cause of death categories are provided. See temporal coverage for more information on which combinations are available for which years.

The cause of death categories are based solely on the underlying cause of death as coded by the International Classification of Diseases. The underlying cause of death is defined by the World Health Organization (WHO) as "the disease or injury which initiated the train of events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury." It is a single value assigned to each death based on the details as entered on the death certificate. When more than one cause is listed, the order in which they are listed can affect which cause is coded as the underlying cause. This means that similar events could be coded with different underlying causes of death depending on variations in how they were entered. Consequently, while underlying cause of death provides a convenient comparison between cause of death categories, it may not capture the full impact of each cause of death as it does not always take into account all conditions contributing to the death.

Daily updates of Covid-19 Global Excess Deaths from the Economist's GitHub repository: https://github.com/TheEconomist/covid-19-the-economist-global-excess-deaths-model

Interpreting estimates

Estimating excess deaths for every country every day since the pandemic began is a complex and difficult task. Rather than being overly confident in a single number, limited data means that we can often only give a very very wide range of plausible values. Focusing on central estimates in such cases would be misleading: unless ranges are very narrow, the 95% range should be reported when possible. The ranges assume that the conditions for bootstrap confidence intervals are met. Please see our tracker page and methodology for more information.

New variants

The Omicron variant, first detected in southern Africa in November 2021, appears to have characteristics that are different to earlier versions of sars-cov-2. Where this variant is now dominant, this change makes estimates uncertain beyond the ranges indicated. Other new variants may do the same. As more data is incorporated from places where new variants are dominant, predictions improve.

Non-reporting countries

Turkmenistan and the Democratic People's Republic of Korea have not reported any covid-19 figures since the start of the pandemic. They also have not published all-cause mortality data. Exports of estimates for the Democratic People's Republic of Korea have been temporarily disabled as it now issues contradictory data: reporting a significant outbreak through its state media, but zero confirmed covid-19 cases/deaths to the WHO.

Acknowledgements

A special thanks to all our sources and to those who have made the data to create these estimates available. We list all our sources in our methodology. Within script 1, the source for each variable is also given as the data is loaded, with the exception of our sources for excess deaths data, which we detail in on our free-to-read excess deaths tracker as well as on GitHub. The gradient booster implementation used to fit the models is aGTBoost, detailed here.

Calculating excess deaths for the entire world over multiple years is both complex and imprecise. We welcome any suggestions on how to improve the model, be it data, algorithm, or logic. If you have one, please open an issue.

The Economist would also like to acknowledge the many people who have helped us refine the model so far, be it through discussions, facilitating data access, or offering coding assistance. A special thanks to Ariel Karlinsky, Philip Schellekens, Oliver Watson, Lukas Appelhans, Berent Å. S. Lunde, Gideon Wakefield, Johannes Hunger, Carol D'Souza, Yun Wei, Mehran Hosseini, Samantha Dolan, Mollie Van Gordon, Rahul Arora, Austin Teda Atmaja, Dirk Eddelbuettel and Tom Wenseleers.

All coding and data collection to construct these models (and make them update dynamically) was done by Sondre Ulvund Solstad. Should you have any questions about them after reading the methodology, please open an issue or contact him at sondresolstad@economist.com.

Suggested citation The Economist and Solstad, S. (corresponding author), 2021. The pandemic’s true death toll. [online] The Economist. Available at: https://www.economist.com/graphic-detail/coronavirus-excess-deaths-estimates [Accessed ---]. First published in the article "Counting the dead", The Economist, issue 20, 2021.

There were 11,480 deaths registered in England and Wales for the week ending November 14, 2025, compared with 11,297 in the previous week. During this time period, the two weeks with the highest number of weekly deaths were in April 2020, with the week ending April 17, 2020, having 22,351 deaths, and the following week 21,997 deaths, a direct result of the COVID-19 pandemic in the UK. Death and life expectancy As of 2022, the life expectancy for women in the UK was just over 82.5 years, and almost 78.6 years for men. Compared with 1765, when average life expectancy was under 39 years, this is a huge improvement in historical terms. Even in the more recent past, life expectancy was less than 47 years at the start of the 20th Century, and was under 70 as recently as the 1950s. Despite these significant developments in the long-term, improvements in life expectancy stalled between 2009/11 and 2015/17, and have even gone into decline since 2020. Between 2020 and 2022, for example, life expectancy at birth fell by 23 weeks for females, and 37 weeks for males. COVID-19 in the UK The first cases of COVID-19 in the United Kingdom were recorded on January 31, 2020, but it was not until a month later that cases began to rise exponentially. By March 5 of this year there were more than 100 cases, rising to 1,000 days later and passing 10,000 cumulative cases by March 26. At the height of the pandemic in late April and early May, there were around six thousand new cases being recorded daily. As of January 2023, there were more than 24.2 million confirmed cumulative cases of COVID-19 recorded in the United Kingdom, resulting in 202,156 deaths.

Number and percentage of deaths, by month and place of residence, 1991 to most recent year.

View daily updates and historical trends for US Coronavirus Deaths Per Day. from United States. Source: Johns Hopkins Center for Systems Science and Engin…

This file contains COVID-19 death counts and rates by month and year of death, jurisdiction of residence (U.S., HHS Region) and demographic characteristics (sex, age, race and Hispanic origin, and age/race and Hispanic origin). United States death counts and rates include the 50 states, plus the District of Columbia. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across jurisdictions. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rate are based on deaths occurring in the specified week and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

Death statistics (i) Number of Deaths for Different Sexes and Crude Death Rate for the Period from 1981 to 2023 (ii) Age-standardised Death Rate (Overall and by Sex) for the Period from 1981 to 2023 (iii) Age-specific Death Rate for Year 2013 and 2023 (iv) Death Rates by Leading Causes of Death for the Period from 2001 to 2023 (v) Number of Deaths by Leading Causes of Death for the Period from 2001 to 2023 (vi) Age-standardised Death Rates by Leading Causes of Death for the Period from 2001 to 2023 (vii) Late Foetal Mortality Rate for the Period from 1981 to 2023 (viii) Perinatal Mortality Rate for the Period from 1981 to 2023 (ix) Neonatal Mortality Rate for the Period from 1981 to 2023 (x) Infant Mortality Rate for the Period from 1981 to 2023 (xi) Number of Maternal Deaths for the Period from 1981 to 2023 (xii) Maternal Mortality Ratio for the Period from 1981 to 2023

NOTE: This dataset has been retired and marked as historical-only. This dataset is a companion to the COVID-19 Daily Cases and Deaths dataset (https://data.cityofchicago.org/d/naz8-j4nc). The major difference in this dataset is that the case, death, and hospitalization corresponding rates per 100,000 population are not those for the single date indicated. They are rolling averages for the seven-day period ending on that date. This rolling average is used to account for fluctuations that may occur in the data, such as fewer cases being reported on weekends, and small numbers. The intent is to give a more representative view of the ongoing COVID-19 experience, less affected by what is essentially noise in the data. All rates are per 100,000 population in the indicated group, or Chicago, as a whole, for “Total” columns. Only Chicago residents are included based on the home address as provided by the medical provider. Cases with a positive molecular (PCR) or antigen test are included in this dataset. Cases are counted based on the date the test specimen was collected. Deaths among cases are aggregated by day of death. Hospitalizations are reported by date of first hospital admission. Demographic data are based on what is reported by medical providers or collected by CDPH during follow-up investigation. Denominators are from the U.S. Census Bureau American Community Survey 1-year estimate for 2018 and can be seen in the Citywide, 2018 row of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa). All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects cases and deaths currently known to CDPH. Numbers in this dataset may differ from other public sources due to definitions of COVID-19-related cases and deaths, sources used, how cases and deaths are associated to a specific date, and similar factors. Data Source: Illinois National Electronic Disease Surveillance System, Cook County Medical Examiner’s Office, U.S. Census Bureau American Community Survey

Vital Statistics: Death Rate: per 1000 Population: West Bengal: Rural data was reported at 5.300 NA in 2020. This records an increase from the previous number of 5.200 NA for 2019. Vital Statistics: Death Rate: per 1000 Population: West Bengal: Rural data is updated yearly, averaging 6.200 NA from Dec 1997 (Median) to 2020, with 23 observations. The data reached an all-time high of 7.700 NA in 1998 and a record low of 5.200 NA in 2019. Vital Statistics: Death Rate: per 1000 Population: West Bengal: Rural data remains active status in CEIC and is reported by Office of the Registrar General & Census Commissioner, India. The data is categorized under India Premium Database’s Demographic – Table IN.GAH003: Vital Statistics: Death Rate: by States.

The average for 2022 based on 196 countries was 8.24 deaths per 1000 people. The highest value was in the Central African Republic: 55.13 deaths per 1000 people and the lowest value was in Qatar: 0.93 deaths per 1000 people. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

Nigeria: Death rate, per 1000 people: The latest value from 2023 is 11.74 deaths per 1000 people, a decline from 11.95 deaths per 1000 people in 2022. In comparison, the world average is 7.70 deaths per 1000 people, based on data from 196 countries. Historically, the average for Nigeria from 1960 to 2023 is 18.72 deaths per 1000 people. The minimum value, 11.74 deaths per 1000 people, was reached in 2023 while the maximum of 26.46 deaths per 1000 people was recorded in 1960.

Actual value and historical data chart for Bangladesh Death Rate Crude Per 1 000 People

Number and percentage of deaths, by place of death (in hospital or non-hospital), 1991 to most recent year.