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

The value for Mortality rate, infant, female (per 1,000 live births) in Botswana was 32.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 105.50 in 1960 and a minimum value of 32.50 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 105.50
1961 102.50
1962 99.60
1963 96.80
1964 94.20
1965 91.60
1966 89.00
1967 86.50
1968 83.90
1969 81.20
1970 78.40
1971 75.60
1972 72.60
1973 69.60
1974 66.50
1975 63.30
1976 60.20
1977 57.10
1978 54.10
1979 51.40
1980 48.80
1981 46.40
1982 44.00
1983 41.90
1984 39.90
1985 38.10
1986 36.50
1987 35.10
1988 34.10
1989 33.60
1990 33.70
1991 34.20
1992 35.10
1993 36.10
1994 37.10
1995 38.10
1996 39.10
1997 40.10
1998 40.80
1999 41.40
2000 41.00
2001 40.40
2002 39.80
2003 39.10
2004 38.20
2005 35.20
2006 34.40
2007 35.80
2008 36.40
2009 36.30
2010 35.70
2011 37.20
2012 36.30
2013 35.60
2014 36.20
2015 35.80
2016 35.50
2017 34.40
2018 33.80
2019 33.20
2020 32.50

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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