In 2023, the death rate in deaths per 1,000 inhabitants in Ethiopia amounted to ****. Between 1960 and 2023, the figure dropped by *****, though the decline followed an uneven course rather than a steady trajectory.

Death rate, crude (per 1,000 people) in Ethiopia was reported at 5.96 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Death rate, crude - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Historical chart and dataset showing Ethiopia death rate by year from 1950 to 2025.

Mortality rate, under-5 (per 1,000 live births) in Ethiopia was reported at 46.5 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Mortality rate, under-5 (per 1,000) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Ethiopia ET: Death Rate: Crude: per 1000 People data was reported at 6.825 Ratio in 2016. This records a decrease from the previous number of 6.997 Ratio for 2015. Ethiopia ET: Death Rate: Crude: per 1000 People data is updated yearly, averaging 18.966 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 25.000 Ratio in 1960 and a record low of 6.825 Ratio in 2016. Ethiopia ET: 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 Ethiopia – Table ET.World Bank.WDI: 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 rate, neonatal (per 1,000 live births) in Ethiopia was reported at 27.4 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Mortality rate; neonatal (per 1;000 live births) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Ethiopia ET: Mortality Rate: Infant: Female: per 1000 Live Births data was reported at 36.000 Ratio in 2016. This records a decrease from the previous number of 37.400 Ratio for 2015. Ethiopia ET: Mortality Rate: Infant: Female: per 1000 Live Births data is updated yearly, averaging 47.400 Ratio from Dec 1990 (Median) to 2016, with 5 observations. The data reached an all-time high of 108.700 Ratio in 1990 and a record low of 36.000 Ratio in 2016. Ethiopia ET: 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 Ethiopia – Table ET.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.

Mortality rate, infant (per 1,000 live births) in Ethiopia was reported at 35.7 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Mortality rate, infant (per 1,000 live births) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Male child mortality rate of Ethiopia went down by 3.51% from 54.2 deaths per thousand live births in 2022 to 52.3 deaths per thousand live births in 2023. Since the 4.64% dip in 2013, male child mortality rate sank by 34.79% in 2023. Child mortality rate is the probability of dying between the exact ages of one and five, if subject to current age-specific mortality rates. The probability is expressed as a rate per 1,000.

Mortality rate, adult, male (per 1,000 male adults) in Ethiopia was reported at 246 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Mortality rate, adult, male (per 1,000 male adults) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Ethiopia ET: Lifetime Risk of Maternal Death: 1 in: Rate Varies by Country data was reported at 64.000 NA in 2015. This records an increase from the previous number of 59.000 NA for 2014. Ethiopia ET: Lifetime Risk of Maternal Death: 1 in: Rate Varies by Country data is updated yearly, averaging 20.500 NA from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 64.000 NA in 2015 and a record low of 12.000 NA in 1992. Ethiopia ET: Lifetime Risk of Maternal Death: 1 in: Rate Varies by Country data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Health Statistics. Life time risk of maternal death is the probability that a 15-year-old female will die eventually from a maternal cause assuming that current levels of fertility and mortality (including maternal mortality) do not change in the future, taking into account competing causes of death.; ; WHO, UNICEF, UNFPA, World Bank Group, and the United Nations Population Division. Trends in Maternal Mortality: 1990 to 2015. Geneva, World Health Organization, 2015; Weighted average;

Ethiopia ET: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data was reported at 43.700 Ratio in 2016. Ethiopia ET: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data is updated yearly, averaging 43.700 Ratio from Dec 2016 (Median) to 2016, with 1 observations. Ethiopia ET: Mortality Rate Attributed to Unsafe Water, Unsafe Sanitation and Lack of Hygiene: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Health Statistics. Mortality rate attributed to unsafe water, unsafe sanitation and lack of hygiene is deaths attributable to unsafe water, sanitation and hygiene focusing on inadequate WASH services per 100,000 population. Death rates are calculated by dividing the number of deaths by the total population. In this estimate, only the impact of diarrhoeal diseases, intestinal nematode infections, and protein-energy malnutrition are taken into account.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Female child mortality rate of Ethiopia declined by 3.59% from 41.8 deaths per thousand live births in 2022 to 40.3 deaths per thousand live births in 2023. Since the 5.00% reduction in 2013, female child mortality rate plummeted by 35.73% in 2023. Child mortality rate is the probability of dying between the exact ages of one and five, if subject to current age-specific mortality rates. The probability is expressed as a rate per 1,000.

Mortality rate, adult, female (per 1,000 female adults) in Ethiopia was reported at 149 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Mortality rate, adult, female (per 1,000 female adults) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Infant mortality rate of Ethiopia fell by 3.51% from 37.0 deaths per thousand live births in 2022 to 35.7 deaths per thousand live births in 2023. Since the 4.22% decline in 2013, infant mortality rate plummeted by 31.61% in 2023. Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.

Ethiopia ET: Mortality Rate: Adult: Male: per 1000 Male Adults data was reported at 245.285 Ratio in 2016. This records a decrease from the previous number of 250.154 Ratio for 2015. Ethiopia ET: Mortality Rate: Adult: Male: per 1000 Male Adults data is updated yearly, averaging 415.954 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 499.054 Ratio in 1960 and a record low of 245.285 Ratio in 2016. Ethiopia ET: Mortality Rate: Adult: Male: per 1000 Male Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Health Statistics. Adult mortality rate, male, is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old male dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) University of California, Berkeley, and Max Planck Institute for Demographic Research. The Human Mortality Database.; Weighted average;

35.7 (deaths per thousand live births) in 2023. Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year.

In 2015, the Ethiopian Federal Ministry of Health (FMOH) developed the Saving Lives through Safe Surgery (SaLTS) initiative to improve national surgical care. Previous work led to development and implementation of 15 surgical key performance indicators (KPIs) to standardize surgical data practices. The objective of this project is to investigate current practices of KPI data collection and assess quality to improve data management and strengthen surgical systems. The first portion of the study documented the surgical data collection process including methods, instruments, and effectiveness at 10 hospitals across 2 regions in Ethiopia. Secondly, data for KPIs of focus [1. Surgical Volume, 2. Perioperative Mortality Rate (POMR), 3. Adverse Anesthetic Outcome (AAO), 4. Surgical Site Infection (SSI), and 5. Safe Surgery Checklist (SSC) Utilization] were compared between registries, KPI reporting forms, and the DHIS2 (district health information system) electronic database for a 6-month period (January—June 2022). Quality was assessed based on data completeness and consistency. The data collection process involved hospital staff recording data elements in registries, quality officers calculating KPIs, completing monthly KPI reporting forms, and submitting data into DHIS2 for the national and regional health bureaus. Data quality verifications revealed discrepancies in consistency at all hospitals, ranging from 1–3 indicators. For all hospitals, average monthly surgical volume was 57 cases, POMR was 0.38% (13/3399), inpatient SSI rate was 0.79% (27/3399), AAO rate was 0.15% (5/3399), and mean SSC utilization monthly was 93% (100% median). Half of the hospitals had incomplete data within the registries, ranging from 2–5 indicators. AAO, SSC, and SSI were commonly missing data in registries. Non-standardized KPI reporting forms contributed significantly to the findings. Facilitators to quality data collection included continued use of registries from previous interventions and use of a separate logbook to document specific KPIs. Delayed rollout of these indicators in each region contributed to issues in data quality. Barriers involved variable indicator recording from different personnel, data collection tools that generate false positives (i.e. completeness of SSC defined as paper form filled out prior to patient discharge) or missing data because of reporting time period (i.e. monthly SSI may miss infections outside of one month), inadequate data elements in registries, and lack of standardized monthly KPI reporting forms. As the FMOH introduces new indicators and changes, we recommend continuous and consistent quality checks and data capacity building, including the use of routinely generated health information for quality improvement projects at the department level.

Ethiopia ET: Mortality Rate: Adult: Female: per 1000 Female Adults data was reported at 193.616 Ratio in 2016. This records a decrease from the previous number of 198.692 Ratio for 2015. Ethiopia ET: Mortality Rate: Adult: Female: per 1000 Female Adults data is updated yearly, averaging 365.610 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 438.492 Ratio in 1960 and a record low of 193.616 Ratio in 2016. Ethiopia ET: Mortality Rate: Adult: Female: per 1000 Female Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank: Health Statistics. Adult mortality rate, female, is the probability of dying between the ages of 15 and 60--that is, the probability of a 15-year-old female dying before reaching age 60, if subject to age-specific mortality rates of the specified year between those ages.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) University of California, Berkeley, and Max Planck Institute for Demographic Research. The Human Mortality Database.; Weighted average;

Background: For decades, health targeted aid in the form of development assistance for health has been an important source of financing health sectors in developing countries. Health sectors in Sub Saharan countries in general and Ethiopia in particular, are even more heavily reliant upon donors. Consequently, a more audible donors support to health sectors was seen during the last four decades, consistent with the donor's response to the global goal of Alma-Ata declaration of "health for all by the year 2000" through primary health care in 1978. Ever since, a massive surge of development assistance for health has followed the out gone of the 2015 United Nations Millennium Declaration Goals in which three out of the eight goals were directly related to health. In spite of the long history of health targeted aid, with an ever increasing volumes, there is an increasing controversy on the extent to which health targeted aid is producing the intended health outcomes in the recipient countries. Despite the vast empirical literatures considering the effect of foreign development aid on economic growth of the recipient countries, systematic evidence that health sector targeted aid improves health outcomes is relatively scarce. The main contribution of this study is, therefore, to present a comprehensive country level, and cross-country evidences on the effect of development assistance for health on health outcomes. Objectives: The overall objective of this study was to analyze the effect of development assistance for health on health outcomes in Ethiopia, and in Sub Saharan Africa. Methods: For the Ethiopian (country level) study, a dynamic time series data analytic approach was employed. A retrospective sample of 36-year observations from 1978 to 2013 was analyzed using an econometric technique - vector error correction model. Beside including time dependency between the variables of interest and allowing for stochastic trends, the model provides valuable information on the existence of long-run and short-run relationships among the variables under study. Furthermore, to estimate the co-integrating relations and the other parameters in the model, the standard procedure of Johansen's approach was used. While development assistance for health expenditure was used as an explanatory variable of interest, life expectancy at birth was used as a dependent variable for the fact that it has long been used with or without mortality measures as health status indicators in the literatures.In the Sub Saharan Africa (cross-country level) study, a dynamic panel data analytic approach was employed using fixed effect, random effect, and the first difference-generalized method of moments estimators in the period confined to the year 1995-2013 over the cross section of 43 SSA countries. While development assistance for health expenditure was used as an explanatory variable of interest here again, infant mortality rate was used for health status measure done for its advantage over other mortality measures in cross-country studies. Results: In Ethiopia, the immediate one and two prior year of development assistance for health was shown to have a significant positive effect on life expectancy at birth. Other things being equal, an increase of development assistance for health expenditure per capita by 1% leads to an improvement in life expectancy at birth by about 0.026 years (P=0.000) in the immediate year following the period, and 0.008 years following the immediate prior two years period (P= 0.025). Similarly, in Sub-Saharan Africa, development assistance for health was found to have a strong negative effect on the reduction of infant mortality rate. The estimates of the study result indicated that during the covered period of study, in the region, a 1% increase in development assistance for health expenditure, which is far less than 10 cents per capita at the mean level, saves the life of two infants per 1000 live births (P=0.000). Conclusion: Contrary to the views of health aid skeptics, this study indicates strong favorable effect of development assistance for health sector in improving health status of people in Sub Saharan Africa in general and the Ethiopia in particular. Recommendations: The policy implication of the current findings is that development assistance for health sector should continue as an interim necessity means. However, domestic health financing system should also be sought, as the targeted countries cannot rely upon external resources continuously for improving the health status of the population. At the same time, the current development assistance stakeholders assumption of targeting facility based primary health care provision should be augmented by a more strong parallel strategy of improving socioeconomic status of the population that promotes sustainable improvement of health status in the targeted countries.