Botswana - Mortality rate, under-5 (per 1,000 live births)

The value for Mortality rate, under-5 (per 1,000 live births) in Botswana was 44.80 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 168.10 in 1960 and a minimum value of 44.80 in 2020.

Definition: Under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified 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 168.10
1961 162.90
1962 158.00
1963 153.20
1964 148.70
1965 144.50
1966 140.20
1967 135.90
1968 131.60
1969 127.20
1970 122.40
1971 117.60
1972 112.60
1973 107.50
1974 102.30
1975 96.90
1976 91.60
1977 86.40
1978 81.40
1979 76.80
1980 72.40
1981 68.30
1982 64.40
1983 60.90
1984 57.70
1985 54.70
1986 52.20
1987 50.10
1988 48.70
1989 48.30
1990 48.90
1991 50.80
1992 53.70
1993 57.10
1994 60.90
1995 65.20
1996 69.20
1997 73.00
1998 76.30
1999 78.70
2000 80.50
2001 80.00
2002 78.30
2003 76.10
2004 72.70
2005 67.00
2006 61.50
2007 58.60
2008 57.60
2009 55.30
2010 51.40
2011 51.90
2012 50.80
2013 49.60
2014 50.20
2015 49.70
2016 49.20
2017 47.80
2018 47.00
2019 45.90
2020 44.80

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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