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

The value for Mortality rate, under-5, male (per 1,000 live births) in Côte d'Ivoire was 85.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 338.80 in 1960 and a minimum value of 85.60 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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 338.80
1961 330.60
1962 322.30
1963 314.40
1964 306.80
1965 298.90
1966 291.20
1967 283.70
1968 276.00
1969 268.60
1970 261.00
1971 253.10
1972 244.60
1973 235.80
1974 226.70
1975 217.60
1976 208.90
1977 200.80
1978 193.60
1979 187.20
1980 181.90
1981 177.40
1982 173.70
1983 170.70
1984 168.40
1985 166.50
1986 165.30
1987 164.50
1988 164.20
1989 164.30
1990 164.60
1991 164.90
1992 165.20
1993 165.40
1994 165.40
1995 164.90
1996 163.70
1997 162.10
1998 160.00
1999 157.40
2000 154.50
2001 151.20
2002 147.70
2003 144.10
2004 140.40
2005 136.40
2006 132.70
2007 128.80
2008 124.80
2009 120.20
2010 116.20
2011 112.80
2012 109.60
2013 106.20
2014 102.60
2015 99.40
2016 96.90
2017 94.30
2018 91.30
2019 88.20
2020 85.60

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