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

The value for Mortality rate, infant, male (per 1,000 live births) in Botswana was 39.50 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 123.20 in 1960 and a minimum value of 39.50 in 2020.

Definition: Infant mortality rate, male is the number of male infants dying before reaching one year of age, per 1,000 male 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 123.20
1961 120.00
1962 116.90
1963 113.90
1964 110.90
1965 108.10
1966 105.30
1967 102.40
1968 99.60
1969 96.70
1970 93.60
1971 90.40
1972 87.00
1973 83.50
1974 79.90
1975 76.30
1976 72.80
1977 69.30
1978 65.90
1979 62.80
1980 59.80
1981 56.90
1982 54.30
1983 51.80
1984 49.40
1985 47.20
1986 45.20
1987 43.50
1988 42.40
1989 41.70
1990 41.70
1991 42.20
1992 43.20
1993 44.20
1994 45.30
1995 46.40
1996 47.50
1997 48.40
1998 49.20
1999 49.60
2000 49.10
2001 48.50
2002 47.70
2003 46.90
2004 45.90
2005 42.40
2006 41.60
2007 43.10
2008 43.90
2009 43.70
2010 43.10
2011 44.90
2012 43.80
2013 43.00
2014 43.70
2015 43.20
2016 43.00
2017 41.80
2018 41.10
2019 40.40
2020 39.50

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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