Central African Republic - Mortality rate, infant (per 1,000 live births)

The value for Mortality rate, infant (per 1,000 live births) in Central African Republic was 77.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 163.90 in 1960 and a minimum value of 77.50 in 2020.

Definition: Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 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 163.90
1961 161.40
1962 158.90
1963 156.40
1964 153.80
1965 150.90
1966 148.20
1967 145.40
1968 142.60
1969 139.90
1970 137.40
1971 135.00
1972 132.70
1973 130.70
1974 128.70
1975 126.90
1976 125.20
1977 123.60
1978 122.00
1979 120.60
1980 119.40
1981 118.30
1982 117.50
1983 116.70
1984 116.20
1985 115.60
1986 115.20
1987 114.90
1988 115.00
1989 115.40
1990 115.60
1991 115.30
1992 114.90
1993 114.30
1994 113.70
1995 113.20
1996 112.70
1997 112.00
1998 111.30
1999 110.60
2000 109.90
2001 109.20
2002 108.50
2003 107.70
2004 106.90
2005 106.10
2006 104.80
2007 103.70
2008 102.50
2009 100.60
2010 99.00
2011 96.70
2012 94.50
2013 93.00
2014 90.50
2015 87.90
2016 85.60
2017 83.80
2018 81.60
2019 79.10
2020 77.50

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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