Congo - Mortality rate, infant, female (per 1,000 live births)

The value for Mortality rate, infant, female (per 1,000 live births) in Congo was 29.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 106.90 in 1960 and a minimum value of 29.50 in 2020.

Definition: 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.

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 106.90
1961 102.90
1962 99.40
1963 96.10
1964 93.10
1965 90.30
1966 87.40
1967 84.80
1968 82.30
1969 80.00
1970 77.80
1971 75.80
1972 73.90
1973 72.20
1974 70.60
1975 69.00
1976 67.60
1977 66.20
1978 64.80
1979 63.40
1980 62.10
1981 60.80
1982 59.50
1983 58.10
1984 56.70
1985 55.40
1986 54.40
1987 53.60
1988 53.30
1989 53.30
1990 53.80
1991 54.70
1992 55.90
1993 57.50
1994 59.30
1995 61.20
1996 63.20
1997 65.00
1998 66.40
1999 66.80
2000 66.30
2001 64.80
2002 62.30
2003 59.10
2004 55.40
2005 51.70
2006 48.20
2007 45.00
2008 42.30
2009 40.30
2010 38.70
2011 37.50
2012 36.60
2013 35.60
2014 34.70
2015 33.70
2016 32.80
2017 31.90
2018 31.10
2019 32.30
2020 29.50

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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