Sierra Leone - Mortality rate, infant (per 1,000 live births)

The value for Mortality rate, infant (per 1,000 live births) in Sierra Leone was 80.10 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 220.30 in 1960 and a minimum value of 80.10 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 220.30
1961 217.20
1962 214.10
1963 211.00
1964 207.80
1965 204.80
1966 201.60
1967 198.60
1968 195.60
1969 192.80
1970 189.90
1971 187.30
1972 184.70
1973 182.10
1974 179.50
1975 177.10
1976 174.90
1977 172.80
1978 170.80
1979 168.90
1980 167.10
1981 165.50
1982 164.00
1983 162.40
1984 161.10
1985 159.80
1986 158.50
1987 157.40
1988 156.30
1989 155.30
1990 154.40
1991 153.50
1992 152.50
1993 151.40
1994 150.20
1995 148.70
1996 147.00
1997 145.10
1998 142.90
1999 140.60
2000 138.10
2001 135.60
2002 132.90
2003 130.20
2004 127.20
2005 124.10
2006 120.90
2007 117.60
2008 114.20
2009 110.60
2010 107.20
2011 103.80
2012 100.70
2013 97.70
2014 95.60
2015 95.10
2016 89.70
2017 87.30
2018 84.80
2019 82.40
2020 80.10

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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