In 2023, the number of deaths per 1,000 inhabitants in South Africa was ****. Between 1960 and 2023, the figure dropped by ****, though the decline followed an uneven course rather than a steady trajectory.

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

As of November 16, 2020, a total of 17.577 COVID-19 related casualties were registered in South Africa. Some 14.1 percent of the deaths fell within the age group of 60 to 64 years with, whereas 12.6 percent of whom were aged 55 to 59 passed away due to the diseases caused by the coronavirus. Confirmed coronavirus cases per region in South Africa illustrated Gauteng was hit hardest. As of January 15, 2021, the region with Johannesburg as its capital registered 350,976 individuals with COVID-19 , whereas KwaZulu-Natal and Western Cape had dealt with less cases.

The statistic shows the adult mortality rate in South Africa from 2013 to 2023, by gender. According to the source, the 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 age-specific mortality rates of the specified year between those ages. In 2023, the mortality rate for women was at ****** per 1,000 female adults, while the mortality rate for men was at ****** per 1,000 male adults in South Africa.

Historical dataset showing South Africa death rate by year from 1950 to 2025.

Abstract

This cumulative dataset contains statistics on mortality and causes of death in South Africa covering the period 1997-2020. The mortality and causes of death dataset is part of a regular series published by Stats SA, based on data collected through the civil registration system. This dataset is the most recent cumulative round in the series which began with the separately available dataset Recorded Deaths 1996.

The main objective of this dataset is to outline emerging trends and differentials in mortality by selected socio-demographic and geographic characteristics for deaths that occurred in the registered year and over time. Reliable mortality statistics, are the cornerstone of national health information systems, and are necessary for population health assessment, health policy and service planning; and programme evaluation. They are essential for studying the occurrence and distribution of health-related events, their determinants and management of related health problems. These data are particularly critical for monitoring the Sustainable Development Goals (SDGs) and Agenda 2063 which share the same goal for a high standard of living and quality of life, sound health and well-being for all and at all ages. Mortality statistics are also required for assessing the impact of non-communicable diseases (NCD's), emerging infectious diseases, injuries and natural disasters.

Geographic coverage

The survey has national coverage.

Analysis unit

Individuals

Universe

This dataset is based on information on mortality and causes of death from the South African civil registration system. It covers all death notification forms from the Department of Home Affairs for deaths that occurred in 1997-2020, that reached Stats SA during the 2021/2022 processing phase.

Kind of data

Administrative records

Mode of data collection

Other

Research instrument

The registration of deaths is captured using two instruments: form BI-1663 and form DHA-1663 (Notification/Register of death/stillbirth).

Data appraisal

This cumulative dataset is part of a regular series published by Stats SA and includes all previous rounds in the series (excluding Recorded Deaths 1996). Stats SA only includes one variable to classify the occupation group of the deceased (OccupationGrp) in the current round (1997-2020). Prior to 2016, Stats SA included both occupation group (OccupationGrp) and industry classifcation (Industry) in all previous rounds. Therefore, DataFirst has made the 1997-2015 cumulative round available as a separately downloadable dataset which includes both occupation group and industry classification of the deceased spanning the years 1997-2015.

In 2022, the estimated number of deaths in South Africa reached *******. This was lower compared to the previous year when the deaths in the country reached the highest level since 2002, at *******. From 2006 onwards (except in 2015), the number of fatalities dropped annually until 2017. In 2021, however, the count of deaths jumped significantly due to the global coronavirus (COVID-19) pandemic.

South Africa: Death rate, per 1000 people: The latest value from 2023 is 9.24 deaths per 1000 people, a decline from 9.4 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 South Africa from 1960 to 2023 is 10.64 deaths per 1000 people. The minimum value, 8.23 deaths per 1000 people, was reached in 1990 while the maximum of 14.2 deaths per 1000 people was recorded in 1960.

South Africa ZA: Death Rate: Crude: per 1000 People data was reported at 9.793 Ratio in 2016. This records a decrease from the previous number of 10.102 Ratio for 2015. South Africa ZA: Death Rate: Crude: per 1000 People data is updated yearly, averaging 11.455 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 14.815 Ratio in 1960 and a record low of 8.199 Ratio in 1991. South Africa ZA: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Mortality and causes of death from death notification

In 2023, the average crude death rate in Africa was **** deaths per 1,000 people. The mortality rate on the continent has decreased gradually since the 2000s. In comparison, the death rate stood at roughly **** deaths per 1,000 population in 2000. Decreasing mortality, together with high fertility and rising life expectancy, is a key driver of Africa's population growth.

South Africa ZA: Mortality Rate: Under-5: per 1000 Live Births data was reported at 43.300 Ratio in 2016. This records a decrease from the previous number of 44.100 Ratio for 2015. South Africa ZA: Mortality Rate: Under-5: per 1000 Live Births data is updated yearly, averaging 66.000 Ratio from Dec 1974 (Median) to 2016, with 43 observations. The data reached an all-time high of 125.500 Ratio in 1974 and a record low of 43.300 Ratio in 2016. South Africa ZA: Mortality Rate: Under-5: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Health Statistics. Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified year.; ; Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

In 2023, the infant mortality rate in deaths per 1,000 live births in South Africa was 24.4. Between 1976 and 2023, the figure dropped by 87, though the decline followed an uneven course rather than a steady trajectory.

Abstract

This dataset contains statistics on deaths in South Africa in 2010. The registration of deaths in South Africa is regulated by the Births and Deaths Registration Act, 51 of 1992. The South African Department of Home Affairs (DHA) is responsible for the registration of deaths in South Africa. The data is collected with two instruments: The death register and the medical certificate in respect of death. The staff of the DHA Registrar of Deaths section fills in the former while the medical practitioner attending to the death completes the latter. Causes of death are coded by the Department of Home Affairs according to the tenth revision of the International Classification of Diseases (ICD-10) ICD-10, as required by the World Health Organization for their member countries. The data is used by the Department of Home Affairs to update the Population Register. The forms are sent to Statistics South Africa (Stats SA) for their use for statistical purposes. From the two forms sent to Stats SA, the following data items of the deceased are extracted: place of residence, place of death, date of death, month and year of registration, sex, marital status, occupation, underlying cause of death, whether or not the death was certified by a medical practitioner, and whether or not the deceased died in a health institution or nursing home. From 1991 death notifications do not require data on population group, and therefore this dataset includes death data for all population groups. This dataset excludes 2010 deaths that were not registered, and late registrations which would not have been available to Stats SA in time for the production of the dataset.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

The data covers all deaths that occurred in 2010 and registered at the Department of Home Affairs in South Africa.

Kind of data

Administrative records data [adm]

Mode of data collection

Other [oth]

Research instrument

The data is collected with two instruments: the death register and the medical certificate in respect of death.

Historical dataset showing South Africa infant mortality rate by year from 1950 to 2025.

South Africa ZA: Completeness of Death Registration with Cause-of-Death Information data was reported at 91.000 % in 2009. This records a decrease from the previous number of 92.300 % for 2008. South Africa ZA: Completeness of Death Registration with Cause-of-Death Information data is updated yearly, averaging 70.400 % from Dec 1992 (Median) to 2009, with 5 observations. The data reached an all-time high of 92.300 % in 2008 and a record low of 0.000 % in 1997. South Africa ZA: Completeness of Death Registration with Cause-of-Death Information data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Population and Urbanization Statistics. Completeness of death registration is the estimated percentage of deaths that are registered with their cause of death information in the vital registration system of a country.; ; World Health Organization, Global Health Observatory Data Repository/World Health Statistics (http://apps.who.int/gho/data/node.main.1?lang=en).; Weighted average;

South Africa ZA: Probability of Dying at Age 20-24 Years: per 1000 data was reported at 12.400 Ratio in 2019. This records a decrease from the previous number of 12.900 Ratio for 2018. South Africa ZA: Probability of Dying at Age 20-24 Years: per 1000 data is updated yearly, averaging 19.800 Ratio from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 28.400 Ratio in 2004 and a record low of 12.400 Ratio in 2019. South Africa ZA: Probability of Dying at Age 20-24 Years: per 1000 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank.WDI: Health Statistics. Probability of dying between age 20-24 years of age expressed per 1,000 youths age 20, if subject to age-specific mortality rates of the specified year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted average; 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.

South Africa ZA: Birth Rate: Crude: per 1000 People data was reported at 20.981 Ratio in 2016. This records a decrease from the previous number of 21.297 Ratio for 2015. South Africa ZA: Birth Rate: Crude: per 1000 People data is updated yearly, averaging 30.616 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 40.222 Ratio in 1960 and a record low of 20.981 Ratio in 2016. South Africa ZA: Birth Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Population and Urbanization Statistics. Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

South Africa ZA: Mortality Rate: Infant: Female: per 1000 Live Births data was reported at 30.100 Ratio in 2016. This records a decrease from the previous number of 31.500 Ratio for 2015. South Africa ZA: Mortality Rate: Infant: Female: per 1000 Live Births data is updated yearly, averaging 33.000 Ratio from Dec 1990 (Median) to 2016, with 5 observations. The data reached an all-time high of 41.200 Ratio in 2000 and a record low of 30.100 Ratio in 2016. South Africa ZA: Mortality Rate: Infant: Female: per 1000 Live Births data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Africa – Table ZA.World Bank: Health Statistics. Infant mortality rate, female is the number of female infants dying before reaching one year of age, per 1,000 female live births in a given year.; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Weighted Average; Given that data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. Moreover, they are among the indicators most frequently used to compare socioeconomic development across countries. Under-five mortality rates are higher for boys than for girls in countries in which parental gender preferences are insignificant. Under-five mortality captures the effect of gender discrimination better than infant mortality does, as malnutrition and medical interventions have more significant impacts to this age group. Where female under-five mortality is higher, girls are likely to have less access to resources than boys.

BackgroundTwo World Health Organization comparative assessments rated the quality of South Africa’s 1996 mortality data as low. Since then, focussed initiatives were introduced to improve civil registration and vital statistics. Furthermore, South African cause-of-death data are widely used by research and international development agencies as the basis for making estimates of cause-specific mortality in many African countries. It is hence important to assess the quality of more recent South African data.MethodsWe employed nine criteria to evaluate the quality of civil registration mortality data. Four criteria were assessed by analysing 5.38 million deaths that occurred nationally from 1997–2007. For the remaining five criteria, we reviewed relevant legislation, data repositories, and reports to highlight developments which shaped the current status of these criteria.FindingsNational mortality statistics from civil registration were rated satisfactory for coverage and completeness of death registration, temporal consistency, age/sex classification, timeliness, and sub-national availability. Epidemiological consistency could not be assessed conclusively as the model lacks the discriminatory power to enable an assessment for South Africa. Selected studies and the extent of ill-defined/non-specific codes suggest substantial shortcomings with single-cause data. The latter criterion and content validity were rated unsatisfactory.ConclusionIn a region marred by mortality data absences and deficiencies, this analysis signifies optimism by revealing considerable progress from a dysfunctional mortality data system to one that offers all-cause mortality data that can be adjusted for demographic and health analysis. Additionally, timely and disaggregated single-cause data are available, certified and coded according to international standards. However, without skillfully estimating adjustments for biases, a considerable confidence gap remains for single-cause data to inform local health planning, or to fill gaps in sparse-data countries on the continent. Improving the accuracy of single-cause data will be a critical contribution to the epidemiologic and population health evidence base in Africa.