Rwanda - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in Rwanda was 40.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 341.20 in 1994 and a minimum value of 40.50 in 2020.

Definition: 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.

Source: Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.

See also:

Year Value
1960 221.00
1961 216.20
1962 212.90
1963 210.50
1964 209.60
1965 209.50
1966 210.40
1967 212.30
1968 215.20
1969 218.50
1970 221.90
1971 224.90
1972 228.70
1973 234.10
1974 240.50
1975 246.50
1976 250.70
1977 250.60
1978 245.00
1979 233.80
1980 218.70
1981 202.00
1982 186.60
1983 174.90
1984 166.50
1985 160.00
1986 154.70
1987 150.30
1988 147.10
1989 146.40
1990 150.30
1991 159.50
1992 173.50
1993 190.40
1994 341.20
1995 219.90
1996 224.50
1997 221.70
1998 213.20
1999 200.80
2000 185.20
2001 167.40
2002 149.60
2003 133.50
2004 118.60
2005 105.40
2006 93.90
2007 84.40
2008 76.30
2009 69.60
2010 63.80
2011 58.60
2012 54.90
2013 52.00
2014 49.70
2015 47.70
2016 46.00
2017 44.60
2018 43.40
2019 41.90
2020 40.50

Development Relevance: Mortality rates for different age groups (infants, children, and adults) and overall mortality indicators (life expectancy at birth or survival to a given age) are important indicators of health status in a country. Because data on the incidence and prevalence of diseases are frequently unavailable, mortality rates are often used to identify vulnerable populations. And they are among the indicators most frequently used to compare socioeconomic development across countries.

Limitations and Exceptions: Complete vital registration systems are fairly uncommon in developing countries. Thus estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to registration, census, or survey data. Survey data are subject to recall error, and surveys estimating infant/child deaths require large samples because households in which a birth has occurred during a given year cannot ordinarily be preselected for sampling. Indirect estimates rely on model life tables that may be inappropriate for the population concerned. Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.

Statistical Concept and Methodology: The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A "complete" vital registration system - covering at least 90 percent of vital events in the population - is the best source of age-specific mortality data. Estimates of neonatal, infant, and child mortality tend to vary by source and method for a given time and place. Years for available estimates also vary by country, making comparisons across countries and over time difficult. To make neonatal, infant, and child mortality estimates comparable and to ensure consistency across estimates by different agencies, the United Nations Inter-agency Group for Child Mortality Estimation (UN IGME), which comprises the United Nations Children's Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and other universities and research institutes, developed and adopted a statistical method that uses all available information to reconcile differences. The method uses statistical models to obtain a best estimate trend line by fitting a country-specific regression model of mortality rates against their reference dates.

Aggregation method: Weighted average

Periodicity: Annual

General Comments: 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 ac

Classification

Topic: Health Indicators

Sub-Topic: Mortality