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

The value for Mortality rate, under-5, male (per 1,000 live births) in Haiti was 65.70 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 303.90 in 1960 and a minimum value of 65.70 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
1960 303.90
1961 299.20
1962 294.60
1963 290.10
1964 285.60
1965 280.90
1966 276.20
1967 271.40
1968 266.40
1969 261.40
1970 256.20
1971 250.80
1972 245.40
1973 239.60
1974 234.00
1975 228.20
1976 222.50
1977 217.10
1978 211.50
1979 206.10
1980 200.90
1981 195.70
1982 190.60
1983 185.60
1984 180.90
1985 176.10
1986 171.40
1987 166.90
1988 162.40
1989 158.00
1990 153.70
1991 149.40
1992 145.20
1993 140.80
1994 136.40
1995 131.90
1996 127.40
1997 122.90
1998 118.80
1999 114.80
2000 111.10
2001 107.60
2002 104.30
2003 101.40
2004 98.60
2005 96.10
2006 93.70
2007 91.60
2008 89.50
2009 87.50
2010 209.80
2011 83.50
2012 81.60
2013 79.70
2014 77.70
2015 75.60
2016 73.60
2017 71.40
2018 69.50
2019 67.70
2020 65.70

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