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

The value for Mortality rate, under-5, female (per 1,000 live births) in Côte d'Ivoire was 69.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 296.00 in 1960 and a minimum value of 69.80 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 296.00
1961 288.30
1962 280.70
1963 273.50
1964 266.40
1965 259.80
1966 253.20
1967 246.60
1968 240.30
1969 233.90
1970 227.30
1971 220.30
1972 212.90
1973 205.30
1974 197.20
1975 189.20
1976 181.20
1977 173.80
1978 167.00
1979 161.20
1980 156.40
1981 152.30
1982 148.90
1983 146.00
1984 143.60
1985 142.00
1986 140.80
1987 140.10
1988 139.70
1989 139.90
1990 140.30
1991 140.90
1992 141.50
1993 141.70
1994 141.60
1995 141.10
1996 140.10
1997 138.50
1998 136.50
1999 134.10
2000 131.40
2001 128.30
2002 125.00
2003 121.60
2004 117.90
2005 114.20
2006 110.60
2007 107.00
2008 103.10
2009 99.20
2010 95.80
2011 92.90
2012 90.20
2013 87.30
2014 84.20
2015 81.60
2016 79.50
2017 77.30
2018 74.60
2019 72.00
2020 69.80

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