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

The value for Mortality rate, infant, female (per 1,000 live births) in Zimbabwe was 33.60 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 83.40 in 1960 and a minimum value of 33.60 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 83.40
1961 81.40
1962 79.30
1963 77.00
1964 74.80
1965 72.60
1966 70.50
1967 68.70
1968 67.10
1969 65.80
1970 64.90
1971 64.30
1972 63.90
1973 63.70
1974 63.60
1975 63.70
1976 63.80
1977 63.90
1978 63.70
1979 62.90
1980 61.60
1981 59.50
1982 56.70
1983 53.70
1984 50.70
1985 48.00
1986 45.90
1987 44.70
1988 44.00
1989 43.90
1990 44.20
1991 45.00
1992 46.10
1993 47.40
1994 48.60
1995 49.80
1996 50.00
1997 49.50
1998 48.40
1999 47.10
2000 46.00
2001 45.30
2002 44.90
2003 44.70
2004 45.40
2005 46.00
2006 47.60
2007 48.80
2008 48.70
2009 48.30
2010 46.50
2011 45.40
2012 41.40
2013 39.80
2014 38.20
2015 37.40
2016 36.20
2017 35.40
2018 34.40
2019 33.80
2020 33.60

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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