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

The value for Mortality rate, infant, male (per 1,000 live births) in Malawi was 32.30 as of 2020. As the graph below shows, over the past 55 years this indicator reached a maximum value of 226.10 in 1965 and a minimum value of 32.30 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
1965 226.10
1966 225.30
1967 224.30
1968 223.00
1969 221.60
1970 219.30
1971 215.80
1972 210.80
1973 205.30
1974 199.40
1975 193.40
1976 187.10
1977 180.70
1978 173.90
1979 167.00
1980 161.30
1981 156.60
1982 153.70
1983 153.50
1984 155.40
1985 158.00
1986 159.70
1987 159.80
1988 158.30
1989 155.00
1990 150.50
1991 145.50
1992 140.30
1993 135.40
1994 130.80
1995 127.00
1996 124.00
1997 121.20
1998 117.80
1999 113.30
2000 107.20
2001 99.50
2002 91.00
2003 82.90
2004 76.10
2005 70.80
2006 67.30
2007 65.30
2008 62.00
2009 59.90
2010 57.70
2011 53.80
2012 50.50
2013 46.80
2014 43.40
2015 40.80
2016 38.40
2017 36.50
2018 34.90
2019 33.50
2020 32.30

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 Extrapolations based on outdated surveys may not be reliable for monitoring changes in health status or for comparative analytical work.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