Number of deaths and age-specific mortality rates for selected grouped causes, by age group and sex, 2000 to most recent year.

According to a Chinese survey conducted in January 2022, more than half of the people shared concerns about being killed by sudden cardiac arrest. One percent of the respondents have such concerns every day, while ** percent have occasional concerns. Ironically, younger generations tend to have higher levels of concern over sudden cardiac death than older people.

In the period from 2018 to 2022, the rate of sudden infant death syndrome in the United States was highest in the state of Mississippi. In Mississippi, there were around 222 sudden unexpected infant deaths per 100,000 live births from 2018 to 2022. This statistic shows the rates of sudden unexpected infant death (SUID) in the U.S. from 2018 to 2022, by state.

Provisional counts of the number of deaths registered in England and Wales, by age, sex, region and Index of Multiple Deprivation (IMD), in the latest weeks for which data are available.

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.

In 2022, the rate of sudden infant death syndrome in the United States was around ** per 100,000 live births. This was a significant decrease from a rate of *** per 100,000 live births in the year 1990. This statistic shows the rates of sudden unexpected infant death (SUID) in the U.S. from 1990 to 2022, by cause of death.

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group.

Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak.

Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool

Data includes:

• Date on which the death occurred
• Age group
• 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated
• 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated
• 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster

Additional notes

As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm.

As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category.

On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023.

CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags.

The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON.

“Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results.

Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts.

Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different.

Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported.

Rates for the most recent days are subject to reporting lags

All data reflects totals from 8 p.m. the previous day.

This dataset is subject to change.

In the period from 2018 to 2022, the state with the highest number of deaths from sudden unexpected infant death (SUID) in the United States was Texas. In Texas, there were around 1,671 sudden unexpected infant deaths from 2018 to 2022. This statistic shows the number of sudden unexpected infant deaths in the U.S. from 2018 to 2022, by state.

Analysis of ‘💊 Drug Induced Deaths’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/drug-induced-deathse on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

This data was compiled using the CDC's WONDER database using these parameters:

• Group By: State, Year
• Measures: Deaths, Population, Crude Rate (95% Confidence Interval and Standard Error)
• Underlying Cause of Death: UCD - Drug/Alcohol Induced Causes - Drug Induced Causes
• Show Totals
• Show Zero Values
• Show Suppressed Values

Citation

Centers for Disease Control and Prevention, National Center for Health Statistics. Multiple Cause of Death
1999-2015 on CDC WONDER Online Database, released December, 2016. Data are from the Multiple Cause of Death Files, 1999-2015, as
compiled from data provided by the 57 vital statistics jurisdictions through the Vital Statistics Cooperative Program. Accessed
at http://wonder.cdc.gov/mcd-icd10.html on November 3, 2017.

Caveats

1. As of April 3, 2017, the underlying cause of death has been revised for 125 deaths in 2014. More information:
   http://wonder.cdc.gov/wonder/help/mcd.html#2014-Revision.
2. Circumstances in Georgia for the years 2008 and 2009 have resulted in unusually high death counts for the ICD-10 cause of
   death code R99, "Other ill-defined and unspecified causes of mortality." Caution should be used in interpreting these data.
   More information: http://wonder.cdc.gov/wonder/help/mcd.html#Georgia-Reporting-Anomalies.
3. Circumstances in New Jersey for the year 2009 have resulted in unusually high death counts for the ICD-10 cause of death code
   R99, "Other ill-defined and unspecified causes of mortality" and therefore unusually low death counts in other ICD-10 codes,
   most notably R95, "Sudden Infant Death Syndrome" and X40-X49, "Unintentional poisoning." Caution should be used in
   interpreting these data. More information: http://wonder.cdc.gov/wonder/help/mcd.html#New-Jersey-Reporting-Anomalies.
4. Circumstances in California resulted in unusually high death counts for the ICD-10 cause of death code R99, "Other
   ill-defined and unspecified causes of mortality" for deaths occurring in years 2000 and 2001. Caution should be used in
   interpreting these data. More information: http://wonder.cdc.gov/wonder/help/mcd.html#California-Reporting-Anomalies.
5. Death rates are flagged as Unreliable when the rate is calculated with a numerator of 20 or less. More information:
   http://wonder.cdc.gov/wonder/help/mcd.html#Unreliable.
6. The method used to calculate 95% confidence intervals is documented here: More information:
   http://wonder.cdc.gov/wonder/help/mcd.html#Confidence-Intervals.
7. The method used to calculate standard errors is documented here: More information:
   http://wonder.cdc.gov/wonder/help/mcd.html#Standard-Errors.
8. The population figures for year 2015 are bridged-race estimates of the July 1 resident population, from the Vintage 2015
   postcensal series released by NCHS on June 28, 2016. The population figures for year 2014 are bridged-race estimates of the July
   1 resident population, from the Vintage 2014 postcensal series released by NCHS on June 30, 2015. The population figures for
   year 2013 are bridged-race estimates of the July 1 resident population, from the Vintage 2013 postcensal series released by NCHS
   on June 26, 2014. The population figures for year 2012 are bridged-race estimates of the July 1 resident population, from the
   Vintage 2012 postcensal series released by NCHS on June 13, 2013. Population figures for 2011 are bridged-race estimates of the
   July 1 resident population, from the county-level postcensal Vintage 2011 series released by NCHS on July 18, 2012. Population
   figures for 2010 are April 1 Census counts. The population figures for years 2001 - 2009, are bridged-race estimates of the July
   1 resident population, from the revised intercensal county-level 2000 - 2009 series released by NCHS on October 26, 2012.
   Population figures for 2000 are April 1 Census counts. Population figures for 1999 are from the 1990-1999 intercensal series of
   July 1 estimates. Population figures for Infant Age Groups are the number of live births. Note: Rates and population
   figures for years 2001 - 2009 differ slightly from previously published reports, due to use of the population estimates which
   were available at the time of release.
9. The population figures used in the calculation of death rates for the age group 'under 1 year' are the estimates of the
   resident population that is under one year of age. More information: http://wonder.cdc.gov/wonder/help/mcd.html#Age Group.

Source: http://wonder.cdc.gov/mcd-icd10.html

This dataset was created by Health and contains around 900 samples along with Crude Rate Lower 95% Confidence Interval, Crude Rate Standard Error, technical information and other features such as: - Year - Crude Rate - and more.

How to use this dataset

• Analyze Deaths in relation to Crude Rate Upper 95% Confidence Interval
• Study the influence of State on Crude Rate Lower 95% Confidence Interval
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Health

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Rate (per 1,000,000 children per year), and relative rate and excess deaths (compared to 2019−2020), by year of death, stratified by cause of death (total population estimate = 11,777,798).

In 2022, the rate of sudden infant death syndrome among Hispanics in the United States was around ** per 100,000 live births. This statistic shows the rates of sudden unexpected infant death (SUID) in the U.S. from 2017 to 2022, by race and ethnicity.

For the week ending August 1, 2025, weekly deaths in England and Wales were 902 below the number expected, compared with 983 below what was expected in the previous week. In late 2022 and through early 2023, excess deaths were elevated for a number of weeks, with the excess deaths figure for the week ending January 13, 2023, the highest since February 2021. In the middle of April 2020, at the height of the COVID-19 pandemic, there were almost 12,000 excess deaths a week recorded in England and Wales. It was not until two months later, in the week ending June 19, 2020, that the number of deaths began to be lower than the five-year average for the corresponding week. Most deaths since 1918 in 2020 In 2020, there were 689,629 deaths in the United Kingdom, making that year the deadliest since 1918, at the height of the Spanish influenza pandemic. As seen in the excess death figures, April 2020 was by far the worst month in terms of deaths during the pandemic. The weekly number of deaths for weeks 16 and 17 of that year were 22,351, and 21,997 respectively. Although the number of deaths fell to more usual levels for the rest of that year, a winter wave of the disease led to a high number of deaths in January 2021, with 18,676 deaths recorded in the fourth week of that year. For the whole of 2021, there were 667,479 deaths in the UK, 22,150 fewer than in 2020. Life expectancy in the UK goes into reverse In 2022, life expectancy at birth for women in the UK was 82.6 years, while for men it was 78.6 years. This was the lowest life expectancy in the country for ten years, and came after life expectancy improvements stalled throughout the 2010s, and then declined from 2020 onwards. There is also quite a significant regional difference in life expectancy in the UK. In the London borough of Kensington and Chelsea, for example, the life expectancy for men was 81.5 years, and 86.5 years for women. By contrast, in Blackpool, in North West England, male life expectancy was just 73.1 years, while for women, life expectancy was lowest in Glasgow, at 78 years.

Relative rate of death, per year, over the whole 4 years, and split into the two periods; results stratified by CYP characteristics.

In 2022, sudden infant death syndrome (SIDS) accounted for around 41 percent of sudden unexpected infant deaths in the United States. This statistic shows the distribution of sudden unexpected infant deaths in the U.S. in 2022, by cause.

Used Dutch companies/platforms on Instagram with the number of followers in May 2022.

Ecuador SNGRE: COVID-19: No. of Deaths: To Date data was reported at 35,940.000 Person in 12 Nov 2022. This records an increase from the previous number of 35,938.000 Person for 11 Nov 2022. Ecuador SNGRE: COVID-19: No. of Deaths: To Date data is updated daily, averaging 21,872.000 Person from Mar 2020 (Median) to 12 Nov 2022, with 971 observations. The data reached an all-time high of 35,940.000 Person in 12 Nov 2022 and a record low of 1.000 Person in 13 Mar 2020. Ecuador SNGRE: COVID-19: No. of Deaths: To Date data remains active status in CEIC and is reported by National Risk and Emergency Management Service. The data is categorized under High Frequency Database’s Disease Outbreaks – Table EC.D003: National Risk and Emergency Management Service: Coronavirus Disease 2019 (COVID-2019) (Discontinued). Current day data is released daily between 11AM and 1PM Ecuador Time. Weekend data are updated following Monday morning, Hong Kong Time. Sudden increase on May 10, 2020 data was due to the reclassification of probable death cases to confirmed death cases by COVID-19. As of September 06, deaths by COVID-19 corresponds to the sum of confirmed death cases with a positive RT-PCR test plus probable death cases who are people with symptoms, other laboratory or imaging tests related to COVID-19, without a RT-PCR test.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

A Chinese survey conducted in January 2022 shows that certain occupational groups were more concerned about being killed by sudden cardiac arrest than others. Online streaming hosts, medical professionals, and students were generally deemed more vulnerable by themselves to sudden cardiac death, given the nature of their working hours and pressure. Civil servants and freelancers were relatively less concerned about this matter.

The leading causes of infant death in the United States are congenital malformations, low birth weight, and sudden infant death syndrome. In 2023, congenital malformations accounted for around 20 percent of all infant deaths in the United States. Infant mortality in the United States Infant mortality refers to the death of a child under the age of one. In the United States, there were around 20,577 infant deaths in 2022. However, the infant mortality rate in the United States has decreased steadily over the past few decades. In 1990, the infant mortality rate was 9.4 per 1,000 live births, but had dropped to around 5.4 per 1,000 live births by 2022. Rates of infant mortality do vary depending on the state and region. For example, the infant mortality rate in Mississippi in 2022 was 9.11 per 1,000 live births, compared to a rate of just 3.32 per 1,000 live births in Massachusetts. What is sudden infant death syndrome (SIDS)? Sudden infant death syndrome (SIDS) is the third leading cause of infant death in the United States with a rate of around 40 deaths per 100,000 live births. SIDS is the unexplained death of an infant. In such cases, the baby usually seems to be healthy but suddenly dies, often during sleep. The cause of SIDS is unknown, but may be connected to problems in the brain controlling breathing and waking from sleep. In 2022, there were an estimated 1,531 deaths from SIDS in the United States. Mississippi and Arkansas are the states with the highest rates of sudden unexpected infant death, while Massachusetts and California have the lowest rates.