Côte d'Ivoire - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in Côte d'Ivoire was 77.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 317.90 in 1960 and a minimum value of 77.90 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 317.90
1961 309.90
1962 302.10
1963 294.50
1964 287.10
1965 279.90
1966 272.60
1967 265.70
1968 258.80
1969 251.60
1970 244.50
1971 237.20
1972 229.30
1973 220.90
1974 212.40
1975 203.80
1976 195.50
1977 187.70
1978 180.60
1979 174.50
1980 169.50
1981 165.10
1982 161.60
1983 158.70
1984 156.40
1985 154.50
1986 153.30
1987 152.50
1988 152.20
1989 152.40
1990 152.80
1991 153.20
1992 153.60
1993 153.90
1994 153.80
1995 153.30
1996 152.20
1997 150.60
1998 148.50
1999 146.10
2000 143.30
2001 140.10
2002 136.70
2003 133.10
2004 129.50
2005 125.60
2006 122.00
2007 118.20
2008 114.20
2009 109.90
2010 106.30
2011 103.10
2012 100.10
2013 97.00
2014 93.60
2015 90.80
2016 88.40
2017 86.00
2018 83.20
2019 80.30
2020 77.90

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