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

The value for Mortality rate, under-5, female (per 1,000 live births) in Haiti was 54.90 as of 2020. As the graph below shows, over the past 60 years this indicator reached a maximum value of 275.50 in 1960 and a minimum value of 54.90 in 2020.

Definition: Under-five mortality rate, female is the probability per 1,000 that a newborn female baby will die before reaching age five, if subject to female 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 275.50
1961 270.90
1962 266.50
1963 262.40
1964 258.10
1965 253.80
1966 249.40
1967 244.80
1968 240.20
1969 235.30
1970 230.50
1971 225.50
1972 220.50
1973 215.40
1974 210.10
1975 205.00
1976 199.80
1977 194.50
1978 189.50
1979 184.70
1980 180.00
1981 175.20
1982 170.50
1983 165.70
1984 161.20
1985 156.70
1986 152.30
1987 148.20
1988 144.10
1989 140.10
1990 136.10
1991 132.20
1992 128.10
1993 124.00
1994 120.00
1995 115.90
1996 111.80
1997 107.80
1998 103.80
1999 100.00
2000 96.40
2001 93.00
2002 89.90
2003 87.20
2004 84.70
2005 82.40
2006 80.30
2007 78.30
2008 76.40
2009 74.60
2010 197.10
2011 71.00
2012 69.30
2013 67.50
2014 65.80
2015 63.90
2016 62.00
2017 60.20
2018 58.30
2019 56.60
2020 54.90

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