In 2019, the leading causes of death worldwide were ischemic heart disease, stroke, and chronic obstructive pulmonary disease (COPD). That year, ischemic heart disease and stroke accounted for a combined ** percent of all deaths worldwide. Although the leading causes of death worldwide vary by region and country, heart disease is a consistent leading cause of death regardless of income, development, size, or location. Heart disease In 2019, around **** million people worldwide died from ischemic heart disease. In comparison, around **** million people died from lung cancer that year, while *** million died from diabetes. The countries with the highest rates of death due to heart attack and other ischemic heart diseases are Lithuania, Russia, and Slovakia. Although some risk factors for heart disease, such as age and genetics, are unmodifiable, the likelihood of developing heart disease can be greatly reduced through a healthy lifestyle. The biggest modifiable risk factors for heart disease include smoking, an unhealthy diet, being overweight, and a lack of exercise. In 2019, it was estimated that around *** million deaths worldwide due to ischemic heart disease could be attributed to smoking. The leading causes of death in the United States Just as it is the leading cause of death worldwide, heart disease is also the leading cause of death in the United States. In 2023, heart disease accounted for ** percent of all deaths in the United States. Cancer was the second leading cause of death in the U.S. that year, followed by accidents. As of 2023, the odds that a person in the United States will die from heart disease is * in *. However, rates of death due to heart disease have actually declined in the U.S. over the past couple decades. From 2000 to 2022, there was a *** percent decline in heart disease deaths. On the other hand, deaths from Alzheimer’s disease saw an increase of *** percent over this period. Alzheimer’s disease is currently the sixth leading cause of death in the United States, accounting for **** deaths per 100,000 population in 2023.

In 2019, the leading causes of death globally included ischemic heart disease, stroke and chronic obstructive pulmonary disease (COPD). There were **** million deaths from ischemic heart disease at that time and about **** million deaths caused by stroke. In recent history, increases in life expectancy, increases in population and better standards of living have changed the leading causes of death over time. Non-Communicable Disease Deaths The number of deaths due to non-communicable diseases has remained relatively stable in recent years. A large majority of non-communicable or chronic disease deaths globally are caused by cardiovascular diseases, followed by cancer. Various lifestyle choices cause or exacerbate many of these chronic diseases. Drinking, smoking and lack of exercise can contribute to higher rates of non-communicable diseases and early death. It is estimated that the relative risk of death before the age of 65 was ** times greater among those that smoked and never quit. Infectious Disease Deaths Trends indicate that the number of deaths due to infectious diseases have decreased in recent years. However, infectious diseases still disproportionately impact low- and middle-income countries. In 2021, tuberculosis, malaria and HIV/AIDS were still among the leading causes of death in low-income countries. However, the leading causes of death in upper income countries are almost exclusively non-communicable, chronic conditions.

The COVID-19 pandemic increased the global death rate, reaching *** in 2021, but had little to no significant impact on birth rates, causing population growth to dip slightly. On a global level, population growth is determined by the difference between the birth and death rates, known as the rate of natural change. On a national or regional level, migration also affects population change. Ongoing trends Since the middle of the 20th century, the global birth rate has been well above the global death rate; however, the gap between these figures has grown closer in recent years. The death rate is projected to overtake the birth rate in the 2080s, which means that the world's population will then go into decline. In the future, death rates will increase due to ageing populations across the world and a plateau in life expectancy. Why does this change? There are many reasons for the decline in death and birth rates in recent decades. Falling death rates have been driven by a reduction in infant and child mortality, as well as increased life expectancy. Falling birth rates were also driven by the reduction in child mortality, whereby mothers would have fewer children as survival rates rose - other factors include the drop in child marriage, improved contraception access and efficacy, and women choosing to have children later in life.

The World Health Organization reported 6932591 Coronavirus Deaths since the epidemic began. In addition, countries reported 766440796 Coronavirus Cases. This dataset provides - World Coronavirus Deaths- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Introduction

This dataset contains death rate of different countries from 1960 to 2019.

Acknowledgement

Source: https://data.worldbank.org/indicator/SP.DYN.CDRT.IN

As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had spread to almost every country in the world, and more than 6.86 million people had died after contracting the respiratory virus. Over 1.16 million of these deaths occurred in the United States.

Waves of infections Almost every country and territory worldwide have been affected by the COVID-19 disease. At the end of 2021 the virus was once again circulating at very high rates, even in countries with relatively high vaccination rates such as the United States and Germany. As rates of new infections increased, some countries in Europe, like Germany and Austria, tightened restrictions once again, specifically targeting those who were not yet vaccinated. However, by spring 2022, rates of new infections had decreased in many countries and restrictions were once again lifted.

What are the symptoms of the virus? It can take up to 14 days for symptoms of the illness to start being noticed. The most commonly reported symptoms are a fever and a dry cough, leading to shortness of breath. The early symptoms are similar to other common viruses such as the common cold and flu. These illnesses spread more during cold months, but there is no conclusive evidence to suggest that temperature impacts the spread of the SARS-CoV-2 virus. Medical advice should be sought if you are experiencing any of these symptoms.

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.

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.

Algeria DZ: Number of Deaths Ages 20-24 Years data was reported at 2,017.000 Person in 2019. This records a decrease from the previous number of 2,148.000 Person for 2018. Algeria DZ: Number of Deaths Ages 20-24 Years data is updated yearly, averaging 2,899.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 4,526.000 Person in 1998 and a record low of 2,017.000 Person in 2019. Algeria DZ: Number of Deaths Ages 20-24 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Algeria – Table DZ.World Bank.WDI: Health Statistics. Number of deaths of youths ages 20-24 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

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.

Israel IL: Number of Deaths Ages 20-24 Years data was reported at 188.000 Person in 2019. This records a decrease from the previous number of 190.000 Person for 2018. Israel IL: Number of Deaths Ages 20-24 Years data is updated yearly, averaging 246.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 384.000 Person in 2002 and a record low of 188.000 Person in 2019. Israel IL: Number of Deaths Ages 20-24 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Israel – Table IL.World Bank.WDI: Health Statistics. Number of deaths of youths ages 20-24 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

The average for 2022 based on 195 countries was 8.37 deaths per 1000 people. The highest value was in Ukraine: 21.4 deaths per 1000 people and the lowest value was in Qatar: 1.08 deaths per 1000 people. The indicator is available from 1960 to 2022. Below is a chart for all countries where data are available.

Trinidad and Tobago TT: Number of Deaths Ages 20-24 Years data was reported at 123.000 Person in 2019. This records a decrease from the previous number of 128.000 Person for 2018. Trinidad and Tobago TT: Number of Deaths Ages 20-24 Years data is updated yearly, averaging 160.000 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 258.000 Person in 2008 and a record low of 123.000 Person in 2019. Trinidad and Tobago TT: Number of Deaths Ages 20-24 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Trinidad and Tobago – Table TT.World Bank.WDI: Health Statistics. Number of deaths of youths ages 20-24 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Germany DE: Number of Deaths Ages 15-19 Years data was reported at 923.000 Person in 2019. This records a decrease from the previous number of 942.000 Person for 2018. Germany DE: Number of Deaths Ages 15-19 Years data is updated yearly, averaging 1,632.000 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 2,544.000 Person in 1990 and a record low of 923.000 Person in 2019. Germany DE: Number of Deaths Ages 15-19 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Health Statistics. Number of deaths of adolescents ages 15-19 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Male adult mortality rate of Bulgaria jumped by 13.71% from 206.1 deaths per 1,000 male adults in 2020 to 234.4 deaths per 1,000 male adults in 2021. Since the 0.99% fall in 2019, male adult mortality rate shot up by 28.68% in 2021. Adult mortality rate is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old dying before reaching age 60, if subject to current age-specific mortality rates between those ages.

As of 2023, the countries with the highest death rates worldwide were Monaco, Bulgaria, and Latvia. In these countries, there were ** to ** deaths per 1,000 people. The country with the lowest death rate is Qatar, where there is just *** death per 1,000 people. Leading causes of death The leading causes of death worldwide are, by far, cardiovascular diseases, accounting for ** percent of all deaths in 2021. That year, there were **** million deaths worldwide from ischaemic heart disease and **** million from stroke. Interestingly, a worldwide survey from that year found that people greatly underestimate the proportion of deaths caused by cardiovascular disease, but overestimate the proportion of deaths caused by suicide, interpersonal violence, and substance use disorders. Death in the United States In 2023, there were around **** million deaths in the United States. The leading causes of death in the United States are currently heart disease and cancer, accounting for a combined ** percent of all deaths in 2023. Lung and bronchus cancer is the deadliest form of cancer worldwide, as well as in the United States. In the U.S. this form of cancer is predicted to cause around ****** deaths among men alone in the year 2025. Prostate cancer is the second-deadliest cancer for men in the U.S. while breast cancer is the second deadliest for women. In 2023, the tenth leading cause of death in the United States was COVID-19. Deaths due to COVID-19 resulted in a significant rise in the total number of deaths in the U.S. in 2020 and 2021 compared to 2019, and it was the third leading cause of death in the U.S. during those years.

Female adult mortality rate of Georgia climb by 1.57% from 72.8 deaths per 1,000 female adults in 2022 to 74.0 deaths per 1,000 female adults in 2023. Since the 2.78% decrease in 2019, female adult mortality rate dipped by 2.05% in 2023. Adult mortality rate is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old dying before reaching age 60, if subject to current age-specific mortality rates between those ages.

Life table data for "Bounce backs amid continued losses: Life expectancy changes since COVID-19"

cc-by Jonas Schöley, José Manuel Aburto, Ilya Kashnitsky, Maxi S. Kniffka, Luyin Zhang, Hannaliis Jaadla, Jennifer B. Dowd, and Ridhi Kashyap. "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

These are CSV files of life tables over the years 2015 through 2021 across 29 countries analyzed in the paper "Bounce backs amid continued losses: Life expectancy changes since COVID-19".

40-lifetables.csv

Life table statistics 2015 through 2021 by sex, region and quarter with uncertainty quantiles based on Poisson replication of death counts. Actual life tables and expected life tables (under the assumption of pre-COVID mortality trend continuation) are provided.

30-lt_input.csv

Life table input data.

id: unique row identifier

region_iso: iso3166-2 region codes

sex: Male, Female, Total

year: iso year

age_start: start of age group

age_width: width of age group, Inf for age_start 100, otherwise 1

nweeks_year: number of weeks in that year, 52 or 53

death_total: number of deaths by any cause

population_py: person-years of exposure (adjusted for leap-weeks and missing weeks in input data on all cause deaths)

death_total_nweeksmiss: number of weeks in the raw input data with at least one missing death count for this region-sex-year stratum. missings are counted when the week is implicitly missing from the input data or if any NAs are encounted in this week or if age groups are implicitly missing for this week in the input data (e.g. 40-45, 50-55)

death_total_minnageraw: the minimum number of age-groups in the raw input data within this region-sex-year stratum

death_total_maxnageraw: the maximum number of age-groups in the raw input data within this region-sex-year stratum

death_total_minopenageraw: the minimum age at the start of the open age group in the raw input data within this region-sex-year stratum

death_total_maxopenageraw: the maximum age at the start of the open age group in the raw input data within this region-sex-year stratum

death_total_source: source of the all-cause death data

death_total_prop_q1: observed proportion of deaths in first quarter of year

death_total_prop_q2: observed proportion of deaths in second quarter of year

death_total_prop_q3: observed proportion of deaths in third quarter of year

death_total_prop_q4: observed proportion of deaths in fourth quarter of year

death_expected_prop_q1: expected proportion of deaths in first quarter of year

death_expected_prop_q2: expected proportion of deaths in second quarter of year

death_expected_prop_q3: expected proportion of deaths in third quarter of year

death_expected_prop_q4: expected proportion of deaths in fourth quarter of year

population_midyear: midyear population (July 1st)

population_source: source of the population count/exposure data

death_covid: number of deaths due to covid

death_covid_date: number of deaths due to covid as of

death_covid_nageraw: the number of age groups in the covid input data

ex_wpp_estimate: life expectancy estimates from the World Population prospects for a five year period, merged at the midpoint year

ex_hmd_estimate: life expectancy estimates from the Human Mortality Database

nmx_hmd_estimate: death rate estimates from the Human Mortality Database

nmx_cntfc: Lee-Carter death rate projections based on trend in the years 2015 through 2019

Deaths

source:

STMF input data series (https://www.mortality.org/Public/STMF/Outputs/stmf.csv)

ONS for GB-EAW pre 2020

CDC for US pre 2020

STMF:

harmonized to single ages via pclm

pclm iterates over country, sex, year, and within-year age grouping pattern and converts irregular age groupings, which may vary by country, year and week into a regular age grouping of 0:110

smoothing parameters estimated via BIC grid search seperately for every pclm iteration

last age group set to [110,111)

ages 100:110+ are then summed into 100+ to be consistent with mid-year population information

deaths in unknown weeks are considered; deaths in unknown ages are not considered

ONS:

data already in single ages

ages 100:105+ are summed into 100+ to be consistent with mid-year population information

PCLM smoothing applied to for consistency reasons

CDC:

The CDC data comes in single ages 0:100 for the US. For 2020 we only have the STMF data in a much coarser age grouping, i.e. (0, 1, 5, 15, 25, 35, 45, 55, 65, 75, 85+). In order to calculate life-tables in a manner consistent with 2020, we summarise the pre 2020 US death counts into the 2020 age grouping and then apply the pclm ungrouping into single year ages, mirroring the approach to the 2020 data

Population

source:

for years 2000 to 2019: World Population Prospects 2019 single year-age population estimates 1950-2019

for year 2020: World Population Prospects 2019 single year-age population projections 2020-2100

mid-year population

mid-year population translated into exposures:

if a region reports annual deaths using the Gregorian calendar definition of a year (365 or 366 days long) set exposures equal to mid year population estimates

if a region reports annual deaths using the iso-week-year definition of a year (364 or 371 days long), and if there is a leap-week in that year, set exposures equal to 371/364*mid_year_population to account for the longer reporting period. in years without leap-weeks set exposures equal to mid year population estimates. further multiply by fraction of observed weeks on all weeks in a year.

COVID deaths

source: COVerAGE-DB (https://osf.io/mpwjq/)

the data base reports cumulative numbers of COVID deaths over days of a year, we extract the most up to date yearly total

External life expectancy estimates

source:

World Population Prospects (https://population.un.org/wpp/Download/Files/1_Indicators%20(Standard)/CSV_FILES/WPP2019_Life_Table_Medium.csv), estimates for the five year period 2015-2019

Human Mortality Database (https://mortality.org/), single year and age tables

Germany DE: Cause of Death: by Non-Communicable Diseases: % of Total data was reported at 90.598 % in 2019. This records a decrease from the previous number of 91.046 % for 2015. Germany DE: Cause of Death: by Non-Communicable Diseases: % of Total data is updated yearly, averaging 91.273 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 91.869 % in 2000 and a record low of 90.598 % in 2019. Germany DE: Cause of Death: by Non-Communicable Diseases: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;

Germany DE: Cause of Death: by Injury: % of Total data was reported at 4.642 % in 2019. This records an increase from the previous number of 3.947 % for 2015. Germany DE: Cause of Death: by Injury: % of Total data is updated yearly, averaging 4.032 % from Dec 2000 (Median) to 2019, with 4 observations. The data reached an all-time high of 4.642 % in 2019 and a record low of 3.868 % in 2010. Germany DE: Cause of Death: by Injury: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Injuries include unintentional and intentional injuries.;Derived based on the data from Global Health Estimates 2020: Deaths by Cause, Age, Sex, by Country and by Region, 2000-2019. Geneva, World Health Organization; 2020. Link: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-death;Weighted average;