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

The value for Mortality rate, under-5, male (per 1,000 live births) in Malawi was 42.70 as of 2020. As the graph below shows, over the past 55 years this indicator reached a maximum value of 371.60 in 1965 and a minimum value of 42.70 in 2020.

Definition: Under-five mortality rate, male is the probability per 1,000 that a newborn male baby will die before reaching age five, if subject to male 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
1965 371.60
1966 370.30
1967 369.00
1968 367.10
1969 365.00
1970 361.60
1971 356.00
1972 348.60
1973 340.00
1974 330.80
1975 321.40
1976 311.70
1977 301.50
1978 290.70
1979 279.30
1980 270.40
1981 262.60
1982 258.10
1983 257.90
1984 261.30
1985 265.90
1986 269.20
1987 269.90
1988 267.80
1989 263.30
1990 257.00
1991 248.90
1992 240.60
1993 232.70
1994 225.40
1995 218.90
1996 213.90
1997 209.20
1998 203.20
1999 195.00
2000 184.00
2001 169.80
2002 154.30
2003 139.90
2004 127.60
2005 118.20
2006 111.70
2007 107.20
2008 101.60
2009 96.30
2010 90.90
2011 84.00
2012 76.70
2013 69.10
2014 63.00
2015 58.40
2016 54.30
2017 50.70
2018 47.50
2019 44.90
2020 42.70

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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