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

The value for Mortality rate, infant, female (per 1,000 live births) in Zambia was 37.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 114.00 in 1960 and a minimum value of 37.80 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 114.00
1961 112.10
1962 110.30
1963 108.80
1964 107.60
1965 106.70
1966 106.30
1967 105.90
1968 105.30
1969 104.10
1970 102.20
1971 99.70
1972 96.70
1973 93.70
1974 91.10
1975 89.10
1976 88.10
1977 87.90
1978 88.10
1979 88.50
1980 89.00
1981 89.40
1982 89.80
1983 90.70
1984 92.40
1985 94.50
1986 96.70
1987 98.70
1988 100.00
1989 100.70
1990 100.90
1991 100.70
1992 100.00
1993 98.70
1994 96.70
1995 94.50
1996 92.60
1997 91.00
1998 89.20
1999 87.10
2000 83.90
2001 79.10
2002 73.30
2003 67.60
2004 61.70
2005 56.80
2006 53.50
2007 51.90
2008 49.80
2009 48.30
2010 46.70
2011 45.70
2012 44.80
2013 42.50
2014 41.90
2015 42.70
2016 41.50
2017 40.20
2018 39.90
2019 38.90
2020 37.80

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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