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

The value for Mortality rate, infant, female (per 1,000 live births) in Senegal was 25.40 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 120.40 in 1965 and a minimum value of 25.40 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 120.00
1961 119.90
1962 120.00
1963 120.10
1964 120.30
1965 120.40
1966 120.20
1967 119.90
1968 119.30
1969 118.40
1970 117.20
1971 115.40
1972 113.30
1973 110.80
1974 107.90
1975 104.60
1976 101.00
1977 97.30
1978 93.80
1979 90.60
1980 87.80
1981 85.60
1982 83.50
1983 81.40
1984 79.10
1985 76.50
1986 73.60
1987 70.70
1988 68.20
1989 66.30
1990 64.90
1991 64.20
1992 63.90
1993 64.00
1994 64.30
1995 64.40
1996 64.60
1997 64.40
1998 63.90
1999 62.70
2000 60.90
2001 58.50
2002 55.70
2003 52.80
2004 50.10
2005 47.40
2006 45.00
2007 42.80
2008 40.80
2009 39.10
2010 37.50
2011 36.00
2012 34.60
2013 33.30
2014 31.90
2015 30.60
2016 29.30
2017 28.20
2018 27.10
2019 26.20
2020 25.40

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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